{ "schema_version": "1.0", "content_version": "latest", "system_name": "Research Operating System (Research OS)", "description": "Canonical machine-readable manifest and index of catalogued research projects, evaluated candidates, datasets, and empirical evidence.", "published_at": "2026-09-30T08:06:09.501Z", "api_base_url": "/api", "entrypoints": { "manifest": "/research-manifest.json", "llms_txt": "/llms.txt", "llms_full_txt": "/llms-full.txt", "system_guide": "/AI_README.md", "operating_rules": "/AGENTS.md", "mcp_endpoint": "/mcp", "mcp_manifest": "/mcp/manifest.json" }, "endpoints": { "research": "/api/research", "candidates": "/api/candidates", "datasets": "/api/datasets", "literature": "/api/literature", "documents": "/api/documents", "projects": "/api/projects", "experiments": "/api/experiments", "findings": "/api/findings", "evidence": "/api/evidence", "sources": "/api/sources", "topics": "/api/topics", "signals": "/api/signals", "timeline": "/api/timeline", "search": "/api/search", "mcp": "/api/mcp" }, "schemas": { "topics": "/schemas/topic.schema.json", "signals": "/schemas/signal.schema.json", "candidates": "/schemas/candidate.schema.json", "datasets": "/schemas/dataset.schema.json", "literature": "/schemas/literature.schema.json", "documents": "/schemas/document.schema.json", "projects": "/schemas/project.schema.json", "experiments": "/schemas/experiment.schema.json", "findings": "/schemas/finding.schema.json", "evidence": "/schemas/evidence.schema.json", "sources": "/schemas/source.schema.json", "timeline": "/schemas/timeline-event.schema.json" }, "counts": { "topics": 5, "signals": 9, "candidates": 8, "datasets": 7, "literature": 5, "documents": 2, "projects": 0, "experiments": 0, "findings": 0, "evidence": 14, "sources": 6, "timeline": 3 }, "entities": { "topics": [ { "schema_version": "1.0", "id": "topic-energy-transition-electrification", "name": "Transisi Energi, Elektrifikasi & Dekarbonisasi Industri", "slug": "energy-transition-electrification", "domain": "infrastructure", "description": "Eksplorasi disparitas kualitas elektrifikasi rumah tangga, elastisitas konsumsi listrik industri vs rumah tangga, dinamika captive power manufaktur, dan evaluasi kesiapan bauran energi baru terbarukan (EBT) daerah.", "keywords": [ "transisi-energi", "rasio-elektrifikasi", "captive-power", "energi-terbarukan", "statistik-listrik", "pln", "susenas", "podes", "pdrb" ], "related_topics": [ "topic-structural-transformation", "topic-poverty-vulnerability" ] }, { "schema_version": "1.0", "id": "topic-food-security-inflation", "name": "Ketahanan Pangan, Nilai Tukar Petani & Inflasi Volatile Foods", "slug": "food-security-inflation", "domain": "agriculture", "description": "Menghubungkan sisi hulu produksi pertanian (KSA padi, Nilai Tukar Petani/NTP) dengan stabilitas harga konsumen dan inflasi makanan (IHK Volatile Foods) di 90 kota.", "keywords": [ "ketahanan-pangan", "inflasi-makanan", "nilai-tukar-petani", "produksi-padi", "ihk", "volatile-foods" ], "related_topics": [ "topic-poverty-vulnerability", "topic-structural-transformation" ] }, { "schema_version": "1.0", "id": "topic-human-capital-development", "name": "Modal Manusia & Akses Layanan Dasar (Pembangunan Manusia)", "slug": "human-capital-development", "domain": "social", "description": "Evaluasi pencapaian Indeks Pembangunan Manusia (IPM) pada tingkat 514 Kabupaten/Kota di Indonesia berdasarkan dimensi kesehatan (UHH), pendidikan (RLS/HLS), dan standar hidup layak.", "keywords": [ "indeks-pembangunan-manusia", "ipm", "angka-harapan-hidup", "rata-rata-lama-sekolah", "pengeluaran-riil", "ketimpangan-spasial" ], "related_topics": [ "topic-poverty-vulnerability" ] }, { "schema_version": "1.0", "id": "topic-poverty-vulnerability", "name": "Sosio-Ekonomi, Kemiskinan & Kerentanan Wilayah", "slug": "poverty-vulnerability", "domain": "social", "description": "Eksplorasi dinamika kemiskinan, ketimpangan pengeluaran (Gini Ratio), garis kemiskinan, dan kerentanan ekonomi regional antar-provinsi dan kabupaten/kota di Indonesia.", "keywords": [ "kemiskinan", "gini-ratio", "garis-kemiskinan", "pengangguran", "susenas", "sakernas" ], "related_topics": [ "topic-human-capital-development", "topic-food-security-inflation" ] }, { "schema_version": "1.0", "id": "topic-structural-transformation", "name": "Transformasi Struktural, Pertumbuhan PDRB & Ketenagakerjaan", "slug": "structural-transformation", "domain": "economy", "description": "Analisis produktivitas sektoral PDRB ADHK 2010 (industri, pertanian, perdagangan), elastisitas penyerapan tenaga kerja (Sakernas), serta perdagangan luar negeri regional.", "keywords": [ "pdrb", "pertumbuhan-ekonomi", "transformasi-struktural", "industri-pengolahan", "ketenagakerjaan", "ekspor-impor" ], "related_topics": [ "topic-poverty-vulnerability", "topic-food-security-inflation" ] } ], "signals": [ { "schema_version": "1.0", "id": "sig-captive-power-shift", "topic_id": "topic-energy-transition-electrification", "type": "statistical", "source_id": "src-bps", "provenance": { "acquisition_method": "bps_mcp", "source_type": "bps_mcp", "source_name": "BPS Statistik Listrik & Industri Manufaktur Besar Sedang", "retrieved_at": "2026-09-13", "query_or_tool": "BPS MCP bps-statistics query captive power & industri IBS", "verification_status": "partially-verified" }, "observation": "Survei IBS dan Publikasi Statistik Captive Power BPS memperlihatkan konsentrasi kapasitas pembangkit mandiri industri manufaktur di kawasan industri, dipengaruhi oleh struktur tarif dan tingkat keandalan pasokan lokal.", "confidence": "medium", "period": "2014–2024", "geography": "Sentra Kawasan Industri Manufaktur (Jawa, Sumatera, Sulawesi)" }, { "schema_version": "1.0", "id": "sig-ebt-regional-gap", "topic_id": "topic-energy-transition-electrification", "type": "statistical", "source_id": "src-den", "provenance": { "acquisition_method": "file", "source_type": "file", "source_name": "Dewan Energi Nasional (DEN)", "retrieved_at": "2026-09-13", "query_or_tool": "Audit dokumen fisik PDF Buku Bauran Energi DEN 2022 & Repositori Perda RUED", "verification_status": "partially-verified" }, "observation": "Evaluasi implementasi RUED-P oleh Dewan Energi Nasional menunjukkan disparitas lebar antara target bauran EBT daerah dan realisasi di lapangan, dengan kendala utama integrasi jaringan transmisi dan kapasitas fiskal daerah.", "confidence": "medium", "period": "2015–2024", "geography": "34 Provinsi" }, { "schema_version": "1.0", "id": "sig-electrification-quality-gap", "topic_id": "topic-energy-transition-electrification", "type": "statistical", "source_id": "src-bps", "provenance": { "acquisition_method": "bps_mcp", "source_type": "bps_mcp", "source_name": "BPS Susenas & Podes", "retrieved_at": "2026-09-13", "query_or_tool": "BPS MCP get_static_table 1555 & Podes 1759", "verification_status": "verified" }, "observation": "Klaim Rasio Elektrifikasi administratif mencapai >99,7%, namun mikrodata Susenas dan Podes mengindikasikan disparitas kualitas nyata: banyak rumah tangga di daerah 3T masih mengandalkan penerangan non-PLN darurat atau panel surya mandiri berdaya rendah tanpa pasokan listrik 24 jam.", "confidence": "high", "period": "1993–2024 (Susenas & Podes)", "geography": "514 Kabupaten/Kota" }, { "schema_version": "1.0", "id": "sig-food-price-volatility", "topic_id": "topic-food-security-inflation", "type": "statistical", "source_id": "src-bps", "provenance": { "acquisition_method": "bps_mcp", "source_type": "bps_mcp", "source_name": "BPS Inflasi IHK", "retrieved_at": "2026-03-01", "query_or_tool": "BPS MCP find_variable inflasi kelompok makanan 90 kota", "verification_status": "verified" }, "observation": "Kenaikan indeks harga yang dibayar petani (Ib / Var 12) dan penurunan Nilai Tukar Petani (NTP / Var 10) memiliki transmisi jeda waktu (transmission lag) terhadap lonjakan inflasi kelompok makanan (Var 1890) dan IHK 90 kota (Var 1709) di tingkat konsumen.", "confidence": "high", "period": "2018–2024 (Bulanan)", "geography": "34 Provinsi sentra produksi & 90 Kota IHK" }, { "schema_version": "1.0", "id": "sig-ga-energy-interest", "topic_id": "topic-energy-transition-electrification", "type": "analytics", "source_id": "src-ga", "provenance": { "acquisition_method": "ga_mcp", "source_type": "ga_mcp", "source_name": "Google Analytics 4 Property 553910715", "retrieved_at": "2026-09-13", "query_or_tool": "GA4 RunReport searchTerm query", "verification_status": "verified" }, "observation": "Audit penelusuran digital pada properti Google Analytics (ID 553910715) mencatat 0 query penelusuran untuk kata kunci 'panel surya', 'PLTS atap', dan 'energi terbarukan'. Perumusan riset energi wajib didasarkan penuh pada bukti empiris data resmi BPS dan ESDM.", "confidence": "high", "period": "2024–2026 (All-time tracking)", "geography": "Observed Users Scope", "scope": { "property": "properties/553910715", "audience": "observed_users", "geography": "unknown", "representativeness": "not representative of general Indonesian population" } }, { "schema_version": "1.0", "id": "sig-industrial-electricity-elasticity", "topic_id": "topic-energy-transition-electrification", "type": "statistical", "source_id": "src-bps", "provenance": { "acquisition_method": "bps_mcp", "source_type": "bps_mcp", "source_name": "BPS Statistik Listrik & PDRB", "retrieved_at": "2026-09-13", "query_or_tool": "BPS MCP bps-statistics query tarif industri PLN & PDRB manufaktur", "verification_status": "verified" }, "observation": "Penjualan tenaga listrik PLN golongan Industri (Tarif I) dan Bisnis (Tarif B) menunjukkan korelasi kuat dan elastisitas siklikal mendahului pertumbuhan PDRB sektor manufaktur triwulanan BPS, menjadikannya kandidat sinyal nowcasting frekuensi tinggi.", "confidence": "high", "period": "2010–2024 (Kuartalan & Tahunan)", "geography": "34 Provinsi & Wilayah Distribusi PLN" }, { "schema_version": "1.0", "id": "sig-ipm-district-gap", "topic_id": "topic-human-capital-development", "type": "statistical", "source_id": "src-bps", "provenance": { "acquisition_method": "bps_mcp", "source_type": "bps_mcp", "source_name": "BPS Indeks Pembangunan Manusia", "retrieved_at": "2026-03-01", "query_or_tool": "BPS MCP WebAPI IPM 514 Kabupaten/Kota", "verification_status": "verified" }, "observation": "Kesenjangan Indeks Pembangunan Manusia / IPM (Var 7) pada 514 Kabupaten/Kota menunjukkan perbedaan tajam pada komponen pembatas utama (bottleneck factor), antara angka harapan hidup (Var 3), rata-rata lama sekolah (Var 5), atau daya beli riil (Var 6).", "confidence": "high", "period": "2010–2024 (Tahunan)", "geography": "514 Kabupaten/Kota" }, { "schema_version": "1.0", "id": "sig-pdrb-sectoral-shift", "topic_id": "topic-structural-transformation", "type": "statistical", "source_id": "src-bps", "provenance": { "acquisition_method": "bps_mcp", "source_type": "bps_mcp", "source_name": "BPS PDRB Sektoral ADHK 2010", "retrieved_at": "2026-03-01", "query_or_tool": "BPS MCP WebAPI PDRB ADHK 17 Lapangan Usaha", "verification_status": "verified" }, "observation": "Pergeseran struktur ekonomi dari sektor agraris ke industri pengolahan/jasa tercermin pada laju pertumbuhan PDRB ADHK (Var 291) dan distribusi sektoral (Var 286), namun elastisitas penyerapan tenaga kerja per sektor (Sakernas Var 520/543) bervariasi signifikan antar-daerah.", "confidence": "high", "period": "2010–2024 (Triwulanan & Tahunan)", "geography": "34/38 Provinsi" }, { "schema_version": "1.0", "id": "sig-poverty-disparity", "topic_id": "topic-poverty-vulnerability", "type": "statistical", "source_id": "src-bps", "provenance": { "acquisition_method": "bps_mcp", "source_type": "bps_mcp", "source_name": "BPS Kemiskinan & Ketimpangan", "retrieved_at": "2026-03-01", "query_or_tool": "BPS MCP WebAPI Persentase Penduduk Miskin P0 Susenas", "verification_status": "verified" }, "observation": "Kesenjangan persentase penduduk miskin (Var 184) dan Garis Kemiskinan (Var 182) antara perkotaan dan perdesaan, serta antar-provinsi (Jawa vs Luar Jawa, KBI vs KTI), dipengaruhi oleh fluktuasi ketenagakerjaan/TPT (Var 543) dan daya beli riil per kapita.", "confidence": "high", "period": "2010–2024 (Tahunan/Semesteran Maret & September)", "geography": "34/38 Provinsi & 514 Kabupaten/Kota" } ], "candidates": [ { "schema_version": "1.0", "id": "cand-captive-power-industrial-transition", "title": "Tipologi & Prediksi Penetrasi Captive Power Industri Manufaktur Menuju Dekarbonisasi", "topic_id": "topic-energy-transition-electrification", "provenance": { "acquisition_method": "bps_mcp", "source_type": "bps_mcp", "source_name": "BPS Statistik Listrik & Industri Manufaktur IBS", "retrieved_at": "2026-09-13", "query_or_tool": "BPS MCP bps-statistics query variable captive power & IBS", "verification_status": "partially-verified" }, "status": "screening", "problem_statement": "Porsi pembangkit mandiri (captive power berbasis batu bara dan solar) di kawasan industri menyumbang emisi tinggi; diperlukan pemodelan determinan pabrik yang beralih atau mempertahankan pembangkit mandiri vs on-grid PLN/EBT.", "signal_ids": [ "sig-captive-power-shift" ], "potential_dataset_ids": [ "ds-bps-electricity-consumption-generation" ], "potential_target": "Probabilitas adopsi captive power & rasio intensitas listrik mandiri (kWh mandiri / total kWh)", "potential_features": [ "Subsektor Industri Pengolahan KBLI 2 Digit dan 3 Digit", "Jumlah Tenaga Kerja dan Skala Nilai Tambah Bruto Pabrik", "Status Permodalan Perusahaan (PMA / PMDN)", "Tingkat Keandalan Jaringan Listrik Regional (SAIDI / SAIFI PLN)", "Diferensiasi Tarif Tenaga Listrik Industri Regional" ], "scores": { "relevance": 0.85, "data_evidence": 0.88, "impact": 0.82, "data_quality": 0.82, "temporal_spatial_coverage": 0.85, "coverage": 0.85, "ml_potential": 0.88, "novelty": 0.85, "feasibility": 0.8 }, "confidence": "medium", "limitations": [ "Akses mikrodata IBS level perusahaan memerlukan standardisasi pembersihan dan izin khusus data sensus BPS", "Belum tersedianya inventarisasi komprehensif captive power level plant/kawasan industri yang tervalidasi sebelum riset empiris dijalankan" ], "leakage_risks": [ "Hindari penggunaan variabel biaya bahan bakar yang berkolinieritas langsung dengan rasio output captive power" ], "literature_ids": [ "lit-burke-2019-indonesia-electricity", "lit-shehzadi-2024-self-generation", "lit-chojkiewicz-2025-solar-storage-captive", "lit-kassem-2024-electrification-industrial-development" ], "evidence_ids": [ "ev-lit-burke-captive-barrier", "ev-lit-shehzadi-outage-selfgen", "ev-lit-shehzadi-indonesia-generator-losses", "ev-lit-chojkiewicz-captive-coal-scale", "ev-lit-chojkiewicz-solar-storage-lcoe", "ev-lit-kassem-grid-industrial-turnover" ], "research_gap": { "established": "Literatur terkini menunjukkan bahwa pemadaman dan biaya listrik berkaitan dengan keputusan perusahaan manufaktur berinvestasi dalam pembangkit mandiri (Shehzadi & Wetzel, 2024), ekspansi jaringan memiliki korelasi kausal historis terhadap perkembangan industri di Jawa (Kassem, 2024), serta solar plus storage kompetitif secara tekno-ekonomi terhadap captive batu bara baru di Kalimantan (Chojkiewicz et al., 2025).", "uncertain": "Apakah determinan intensitas captive power skala industri berat/kawasan industri berbeda secara struktural dari determinan pembangkit mandiri cadangan (backup generator) generik level perusahaan.", "geographic_gap": "Dalam literatur yang ditelaah, studi empiris terpusat di Jawa (Kassem 2024) atau simulasi tekno-ekonomi satu pulau seperti Kalimantan (Chojkiewicz et al., 2025); belum teridentifikasi dalam literatur yang ditinjau pemetaan tipologi spasial dan intensitas captive power di koridor industri Sulawesi, Maluku Utara, dan Sumatra.", "temporal_gap": "Dinamika lonjakan captive coal pasca-2020 akibat kebijakan hilirisasi mineral belum tercakup dalam analisis panel mikro-empiris pada literatur yang ditinjau.", "data_gap": "Dalam batas penelusuran saat ini, belum teridentifikasi dataset terpadu yang memadukan mikrodata IBS BPS, inventarisasi kapasitas captive plant/smelter, dan metrik keandalan jaringan regional PLN.", "methodological_gap": "Studi terdahulu terpisah antara model keputusan biner survei generik (ESRM Shehzadi & Wetzel 2024) dan simulasi tekno-ekonomi tanpa perilaku adopsi perusahaan (Chojkiewicz et al., 2025); dalam literatur yang ditelaah, belum ada estimasi mikro-empiris terhadap intensitas captive aktual level pabrik.", "proposed_contribution": "Membangun inventarisasi captive power industri manufaktur Indonesia dan memodelkan determinan intensitas captive power level pabrik/subsektor KBLI terhubung dengan karakteristik keandalan jaringan regional." }, "decision": "screening", "decision_reason": "Potensi riset sangat tinggi namun status tetap screening: diperlukan tahap konstruksi dan validasi data inventarisasi captive power sebelum layak dipromosikan menjadi Proyek.", "project_slug": null }, { "schema_version": "1.0", "id": "cand-electricity-industrial-nowcasting", "title": "Nowcasting Pertumbuhan PDRB Industri Pengolahan Provinsi Berbasis Sinyal Aktivitas Industri Frekuensi Tinggi (Provincial Manufacturing Nowcasting)", "topic_id": "topic-structural-transformation", "provenance": { "acquisition_method": "bps_mcp", "source_type": "bps_mcp", "source_name": "BPS WebAPI & Berita Resmi Statistik (BRS)", "retrieved_at": "2026-09-16", "query_or_tool": "BPS WebAPI v1 Var 2267, Var 2346, Var 401, Var 89 & BRS Rilis", "verification_status": "verified" }, "status": "shortlisted", "problem_statement": "Apakah penambahan indikator aktivitas industri frekuensi tinggi yang tersedia pada saat prediksi mampu meningkatkan akurasi nowcast pertumbuhan PDRB industri pengolahan triwulanan tingkat provinsi di Indonesia dibandingkan model acuan benchmark yang hanya menggunakan informasi yang tersedia sebelum periode target?", "signal_ids": [ "sig-pdrb-sectoral-shift" ], "potential_dataset_ids": [ "ds-bps-pdrb-structural-transformation", "ds-bps-electricity-consumption-generation" ], "potential_target": "BPS Var 2267 — PDRB ADHK 2010 Kategori C Industri Pengolahan Triwulanan Menurut 38 Provinsi", "potential_features": [ "BPS Var 2346: Nilai Ekspor Nonmigas Bulanan Menurut Provinsi Asal Barang (proxy aktivitas industri daerah, status CONDITIONAL)", "BPS Var 401: Indeks Produksi Triwulanan Industri Skala Mikro dan Kecil / IMK Menurut Provinsi (status CONDITIONAL)", "Lagged PDRB Manufaktur Triwulan t-1 dan t-2 (benchmark autoregresif)", "BPS Var 89: Indeks Produksi IBS Triwulanan Nasional (kontrol makro)", "BPS Var 2312: Nilai Ekspor Bulanan Hasil Industri Menurut Komoditas (kontrol makro)", "Indeks Kepercayaan Industri (IKI) Kemenperin (kontrol makro sentimen)" ], "scores": { "relevance": 0.88, "data_evidence": 0.9, "impact": 0.85, "data_quality": 0.85, "temporal_spatial_coverage": 0.88, "coverage": 0.88, "ml_potential": 0.85, "novelty": 0.75, "feasibility": 0.8 }, "confidence": "medium", "limitations": [ "Scope Transition: Candidate ini bertransisi dari desain awal nowcasting berbasis listrik industri (electricity-led) menjadi nowcasting manufaktur provinsi yang lebih luas (provincial manufacturing nowcasting); ID candidate 'cand-electricity-industrial-nowcasting' dipertahankan demi menjaga integritas referensi dan identitas repositori", "Electricity Layer BLOCKED sebagai predictor utama real-time high-frequency provincial nowcasting: Data penjualan/konsumsi listrik industri resmi di BPS hanya tersedia tahunan (Var 314 & 859) dengan lag rilis 12 bulan (T+12) dan tidak memiliki panel kuartalan/bulanan per provinsi pada saat prediksi; data kelistrikan historis dan tahunan tetap valid sebagai bukti kontekstual dan analisis struktural terpisah", "BPS Var 2346 (Ekspor Nonmigas Provinsi) diposisikan sebagai proxy aktivitas ekonomi/industri daerah, bukan pengukuran langsung output fisik manufaktur; memuat porsi komoditas ekstraktif di provinsi berbasis sumber daya alam (seperti batubara di Kaltim/Kalsel) sehingga membutuhkan estimasi panel fixed effects dan analisis heterogenitas regional", "BPS WebAPI v1 hanya menyediakan kondisi terkini (current revised state) dan bukan API time-travel/as-of; evaluasi out-of-sample wajib menggunakan first-release values yang direkonstruksi dari dokumen Berita Resmi Statistik (BRS) kontemporer untuk menghindari revision leakage", "BPS Var 2346 berstatus CONDITIONAL sampai modul full vintage ingestion dari dokumen BRS selesai dibangun", "BPS Var 401 (IMK Provinsi) berstatus CONDITIONAL karena verifikasi first-release dan pola revisi historisnya belum selengkap Var 2346 dan Var 2267", "Target BPS Var 2267 terverifikasi pada level sampel vintage BRS, namun basis data vintage historis jangka panjang belum selesai", "Indikator IBS tingkat provinsi (Jabar Var 749, Jateng Var 1817) terhenti pasca-2021 di portal daerah sehingga tidak dapat dijadikan panel provinsi langsung", "Pembangkit mandiri (captive power) industri tidak dicampuradukkan dengan konsumsi listrik jaringan PLN; fenomena captive generator skala besar di luar Jawa memerlukan jalur analisis struktural terpisah", "Tahap pemodelan empiris berstatus GATED sampai dataset vintage historis selesai direkonstruksi" ], "leakage_risks": [ "Revision leakage: Nilai awal ekspor mengalami revisi rutin ke bawah (-0,40% s.d. -13,84%); penggunaan data Current API secara retroaktif membocorkan revisi masa depan ke model peramalan masa lalu", "Look-ahead timing leakage: Hanya observasi yang benar-benar telah dirilis pada cutoff date yang boleh dimasukkan ke dalam information set. Contoh rilis aktual 2024: ekspor Maret 2024 rilis 22 April 2024; PDRB Q1-2024 rilis 6 Mei 2024 dengan lead time 14 hari (bukan 20 hari); jadwal rilis ekspor terbit sekitar pertengahan bulan berdasarkan kalender BRS aktual (bukan selalu tanggal 15)", "Future information leakage: Dilarang melakukan interpolasi artifisial data tahunan ke kuartalan untuk mencegah kebocoran informasi masa depan", "Target leakage: Preprocessing (standardisasi z-score, estimasi faktor MIDAS) harus diestimasi secara ketat hanya menggunakan data in-sample rolling window tanpa membocorkan data target out-of-sample" ], "literature_ids": [ "lit-lehmann-2024-electricity-forecasting", "lit-kassem-2024-electrification-industrial-development" ], "evidence_ids": [ "ev-bps-electricity-nowcasting-feasibility-audit", "ev-bps-provincial-export-imk-nowcasting-audit", "ev-bps-vintage-first-release-revision-audit", "ev-lit-lehmann-electricity-nowcasting-precedent", "ev-lit-kassem-grid-industrial-turnover" ], "research_gap": { "established": "Preseden empiris internasional (Lehmann & Möhrle, 2024 di Bavaria) membuktikan bahwa indikator aktivitas frekuensi tinggi memiliki nilai prediktif signifikan untuk nowcasting produksi industri regional melampaui survei konvensional. Di Indonesia, Kassem (2024) menemukan bukti hubungan kausal jangka panjang antara infrastruktur listrik dan perkembangan manufaktur di Jawa.", "uncertain": "Apakah penambahan indikator aktivitas industri yang tersedia tepat waktu (ekspor nonmigas provinsi Var 2346 dan IMK Var 401) memberikan incremental predictive value yang signifikan terhadap pertumbuhan PDRB manufaktur kuartalan provinsi (Var 2267) dibandingkan benchmark autoregresif lag PDRB dalam information set bebas revision leakage.", "geographic_gap": "Belum ada evaluasi nowcasting PDRB industri regional di Indonesia yang menguji disparitas akurasi antara provinsi sentra manufaktur utama (Jawa, Banten, Kepri) vs provinsi berbasis komoditas ekstraktif.", "temporal_gap": "Dinamika runtun waktu pasca-2020 dan pemekaran 38 provinsi di Indonesia belum dievaluasi dalam kerangka pseudo-out-of-sample nowcasting U-MIDAS real-time.", "data_gap": "Ketiadaan database vintage terstruktur di WebAPI BPS menuntut kompilasi arsip BRS fisik untuk merekonstruksi matriks first-release provinsi tanpa look-ahead bias.", "methodological_gap": "Belum ada studi empiris nowcasting PDRB manufaktur regional Indonesia yang menerapkan kerangka U-MIDAS / mixed-frequency panel yang mematuhi kalender rilis riil BRS secara ketat.", "proposed_contribution": "Membangun kerangka pseudo-out-of-sample provincial manufacturing nowcasting berbasis first-release vintages BRS untuk mengevaluasi incremental predictive value ekspor bulanan provinsi dan IMK terhadap PDRB manufaktur kuartalan 38 provinsi di Indonesia." }, "decision": "shortlisted", "decision_reason": "CONDITIONAL: The original electricity-led provincial manufacturing nowcasting design is blocked as a real-time high-frequency predictor because publicly available electricity data do not provide a sufficiently timely industrial-by-province series. The research agenda remains viable by shifting to a broader provincial manufacturing nowcasting design using quarterly provincial manufacturing GDP as the target and timely activity indicators such as provincial monthly exports and provincial quarterly IMK production as candidate predictors. However, empirical modeling must remain gated until a reproducible historical vintage layer is built from contemporaneous BRS releases and information sets can be reconstructed without revision leakage.", "project_slug": null }, { "schema_version": "1.0", "id": "cand-electrification-quality-disparity", "title": "Deteksi Dini Disparitas Kualitas Elektrifikasi & Akses Energi Rumah Tangga", "topic_id": "topic-energy-transition-electrification", "provenance": { "acquisition_method": "bps_mcp", "source_type": "bps_mcp", "source_name": "BPS Susenas & Podes Panel", "retrieved_at": "2026-09-13", "query_or_tool": "BPS MCP get_static_table 1555 & Podes 1759", "verification_status": "verified" }, "status": "shortlisted", "problem_statement": "Klaim Rasio Elektrifikasi administratif >99% menyamarkan kesenjangan kualitas riil, di mana rumah tangga di daerah 3T masih mengandalkan penerangan non-PLN terbatas tanpa keandalan daya untuk aktivitas produktif.", "signal_ids": [ "sig-electrification-quality-gap" ], "potential_dataset_ids": [ "ds-bps-electricity-access-panel" ], "potential_target": "Rasio Rumah Tangga berpenerangan Non-PLN / Bukan Listrik / Menyalur (Susenas BPS)", "potential_features": [ "PDRB ADHK per Kapita menurut Kabupaten/Kota (Lag t-1)", "Pangsa PDRB Kategori D Provinsi terhadap Total PDRB Provinsi (Lag t-1)", "Persentase Penduduk Miskin P0 Tingkat Kabupaten/Kota (Lag t-1)", "Rasio Desa Berlistrik dan Penerangan Jalan Desa (Podes)", "Topografi Keterisolasian Desa Kepulauan/Pegunungan (Podes)", "Alokasi Belanja Modal Infrastruktur APBD Daerah" ], "scores": { "relevance": 0.9, "data_evidence": 0.95, "impact": 0.88, "data_quality": 0.9, "temporal_spatial_coverage": 0.92, "coverage": 0.92, "ml_potential": 0.82, "novelty": 0.8, "feasibility": 0.9 }, "confidence": "high", "limitations": [ "Survei Podes dilaksanakan tri-tahunan (2014, 2018, 2021, 2024); Triennial Panel Model (4-wave murni) ditetapkan sebagai MODEL UTAMA, sedangkan panel interpolasi tahunan hanya sebagai model sekunder/eksploratif karena missingness 63.64%", "Variabel jarak ke gardu induk tidak tersedia di BPS/publik; diproksikan melalui rasio penerangan jalan desa dan kemudahan transportasi Podes", "Pemekaran 4 DOB Papua (2022) memerlukan penyesuaian kode wilayah referensi MFD BPS baseline 514 kabupaten/kota; 7 kabupaten pemekaran 2014 ditandai dengan flag is_backcasted: true untuk robustness check terpisah" ], "leakage_risks": [ "Variabel kemiskinan (P0) dan PDRB berasal dari tahun yang sama; wajib menggunakan lag time t-1 untuk predictive setup", "Breakdown 17 sektor PDRB kab/kota tidak tersedia seragam via API terpusat; anti target leakage diterapkan via temporal lagging mutlak (t-1) pada PDRB Total Kab/Kota dan PDRB Kategori D Kontrol Provinsi" ], "decision": "shortlisted", "decision_reason": "Dataset Susenas, Podes, dan PDRB 514 kabupaten/kota terverifikasi. Triennial Panel Model (4-gelombang murni) siap menjadi model utama tanpa missingness sintetik, didukung spatial econometrics dan supervised ML. Menunggu persetujuan peneliti untuk promosi.", "project_slug": null }, { "schema_version": "1.0", "id": "cand-food-inflation-nowcasting", "title": "Nowcasting & Peramalan Tekanan Inflasi Volatile Foods Berbasis Indikator Nilai Tukar Petani (NTP)", "topic_id": "topic-food-security-inflation", "provenance": { "acquisition_method": "bps_mcp", "source_type": "bps_mcp", "source_name": "BPS Inflasi IHK & Kerangka Sampel Area Padi", "retrieved_at": "2026-03-05", "query_or_tool": "BPS MCP WebAPI Subject 3 / 1498 / Var 1", "verification_status": "verified" }, "status": "shortlisted", "problem_statement": "Lonjakan inflasi komponen makanan (volatile foods) berdampak langsung pada penurunan daya beli masyarakat rentan dan stabilitas moneter daerah, namun intervensi operasi pasar TPID sering terlambat karena menunggu rilis resmi IHK.", "signal_ids": [ "sig-food-price-volatility" ], "potential_dataset_ids": [ "ds-bps-food-security-inflation-monthly" ], "potential_target": "Inflasi Kelompok Makanan Bulanan MoM / YoY (Var ID 1890) pada 90 Kota IHK", "potential_features": [ "Nilai Tukar Petani Gabungan & Tanaman Pangan (Var ID 10 & 14)", "Indeks Harga Diterima Petani / It (Var ID 11)", "Indeks Harga Dibayar Petani / Ib (Var ID 12)", "Luas Panen & Produksi Padi KSA (Var ID 1498 / 23)", "Inflasi Umum Bulanan Lag 1–3 Bulan (Var ID 1)" ], "scores": { "relevance": 0.95, "data_evidence": 0.9, "impact": 0.95, "data_quality": 0.85, "temporal_spatial_coverage": 0.8, "coverage": 0.8, "ml_potential": 0.85, "novelty": 0.75, "feasibility": 0.85 }, "confidence": "high", "limitations": [ "Perubahan tahun dasar IHK pada awal 2024 membutuhkan penyambungan indeks (splicing)" ], "leakage_risks": [ "Fitur inflasi umum bulan berjalan tidak boleh digunakan untuk memprediksi inflasi kelompok makanan pada bulan yang sama" ], "decision": "shortlisted", "decision_reason": "Data runtun waktu bulanan 2018–2024 (84 bulan × 34 provinsi / 90 kota) sangat ideal untuk pemodelan multivariate time series forecasting (SARIMAX, LSTM, SVR).", "project_slug": null }, { "schema_version": "1.0", "id": "cand-pdrb-structural-nowcasting", "title": "Nowcasting Pertumbuhan PDRB Triwulanan & Tipologi Wilayah Berbasis Produktivitas Sektoral", "topic_id": "topic-structural-transformation", "provenance": { "acquisition_method": "bps_mcp", "source_type": "bps_mcp", "source_name": "BPS PDRB ADHK & Sakernas", "retrieved_at": "2026-03-05", "query_or_tool": "BPS MCP WebAPI PDRB 17 Sektor & TPT Sakernas", "verification_status": "verified" }, "status": "screening", "problem_statement": "Pertumbuhan PDRB triwulanan dirilis BPS dengan jeda 5–6 minggu setelah kuartal berakhir, sehingga pemda dan pelaku bisnis membutuhkan estimasi dini berbasis indikator sektoral berfrekuensi tinggi.", "signal_ids": [ "sig-pdrb-sectoral-shift" ], "potential_dataset_ids": [ "ds-bps-pdrb-structural-transformation" ], "potential_target": "Laju Pertumbuhan PDRB ADHK 2010 Triwulanan (Var ID 291)", "potential_features": [ "PDRB ADHK Sektor Industri Pengolahan, Pertanian, Perdagangan, Konstruksi (Var ID 286)", "PDRB Per Kapita (Var ID 288)", "Distribusi Persentase PDRB Daerah (Var ID 289)", "Tingkat Pengangguran Terbuka & Penyerapan Tenaga Kerja (Var ID 520 / 543)", "Nilai Ekspor dan Impor Daerah (Var ID 8)" ], "scores": { "relevance": 0.85, "data_evidence": 0.85, "impact": 0.85, "data_quality": 0.8, "temporal_spatial_coverage": 0.8, "coverage": 0.8, "ml_potential": 0.75, "novelty": 0.65, "feasibility": 0.75 }, "confidence": "medium", "limitations": [ "Jeda publikasi data triwulanan membuat ukuran sampel per provinsi terbatas pada 60 kuartal (2010–2024)" ], "leakage_risks": [ "Fitur PDRB sektoral adalah komponen penyusun langsung dari total PDRB sehingga nowcasting harus menggunakan data lag atau indikator proksi bulanan" ], "decision": "screening", "decision_reason": "Dataset solid dan siap diolah; perlu formulasi proksi bulanan sebelum masuk ke tahap eksperimen penuh.", "project_slug": null }, { "schema_version": "1.0", "id": "cand-poverty-early-warning", "title": "Deteksi Dini Kerentanan Kemiskinan Daerah Berbasis Indikator Ketenagakerjaan & Garis Kemiskinan", "topic_id": "topic-poverty-vulnerability", "provenance": { "acquisition_method": "bps_mcp", "source_type": "bps_mcp", "source_name": "BPS Susenas Kemiskinan & Gini Ratio", "retrieved_at": "2026-03-05", "query_or_tool": "BPS MCP WebAPI Susenas Maret & September", "verification_status": "verified" }, "status": "shortlisted", "problem_statement": "Angka kemiskinan resmi (P0) dirilis dua kali setahun (Maret & September) dengan jeda publikasi, sementara guncangan ketenagakerjaan dan kenaikan harga kebutuhan pokok memerlukan penargetan bantuan sosial adaptif yang lebih cepat.", "signal_ids": [ "sig-poverty-disparity" ], "potential_dataset_ids": [ "ds-bps-poverty-vulnerability-panel" ], "potential_target": "Persentase Penduduk Miskin (P0 / Var ID 184) atau Klasifikasi Risiko Lonjakan Kemiskinan", "potential_features": [ "Gini Ratio (Var ID 98)", "Garis Kemiskinan Makanan vs Non-Makanan (Var ID 182)", "Tingkat Pengangguran Terbuka / TPT (Var ID 543)", "Pengeluaran Riil per Kapita Disesuaikan (Var ID 6)", "Rata-Rata Lama Sekolah (Var ID 5)", "Angka Harapan Hidup (Var ID 3)" ], "scores": { "relevance": 0.9, "data_evidence": 0.9, "impact": 0.9, "data_quality": 0.85, "temporal_spatial_coverage": 0.85, "coverage": 0.85, "ml_potential": 0.8, "novelty": 0.7, "feasibility": 0.85 }, "confidence": "high", "limitations": [ "Survei Susenas agregat provinsi tidak menangkap disparitas mikro di tingkat desa tanpa integrasi Podes" ], "leakage_risks": [ "Garis kemiskinan dan persentase kemiskinan dihitung dari survei Susenas yang sama sehingga perlu pembagian lag temporal yang ketat" ], "decision": "shortlisted", "decision_reason": "Ketersediaan data panel 34 provinsi × 15 tahun (N×T ≈ 510) dan 514 kabupaten/kota sangat solid untuk pemodelan regresi panel dan klasifikasi risiko dini.", "project_slug": null }, { "schema_version": "1.0", "id": "cand-regional-ebt-readiness-gap", "title": "Evaluasi Kesenjangan Potensi vs Realisasi Pembangkit EBT Daerah (RUED-P Gap)", "topic_id": "topic-energy-transition-electrification", "provenance": { "acquisition_method": "file", "source_type": "file", "source_name": "Kementerian ESDM & Dewan Energi Nasional", "retrieved_at": "2026-09-13", "query_or_tool": "Audit dokumen fisik PDF Buku Bauran Energi DEN 2022 & Laporan HEESI", "verification_status": "partially-verified" }, "status": "screening", "problem_statement": "Rencana Umum Energi Daerah (RUED-P) menargetkan bauran EBT tinggi di tiap provinsi, namun realisasi di lapangan sangat timpang antar-wilayah akibat kendala kapasitas fiskal daerah dan keterbatasan integrasi jaringan transmisi.", "signal_ids": [ "sig-ebt-regional-gap" ], "potential_dataset_ids": [ "ds-esdm-ebt-regional-balance", "ds-bps-electricity-access-panel" ], "potential_target": "Gap Realisasi Bauran EBT terhadap Target RUED (%) & Kapasitas Terpasang EBT per Kapita (kW/kapita)", "potential_features": [ "Potensi Teknis Surya, Air, dan Biomassa Daerah (Geoportal ESDM)", "Kapasitas Fiskal Daerah (Rasio PAD terhadap APBD)", "Cadangan Daya Listrik (Reserve Margin) Sistem Kelistrikan Regional", "Rasio Elektrifikasi Dasar dan Tingkat Kemiskinan Daerah" ], "scores": { "relevance": 0.86, "data_evidence": 0.82, "impact": 0.88, "data_quality": 0.8, "temporal_spatial_coverage": 0.82, "coverage": 0.82, "ml_potential": 0.8, "novelty": 0.82, "feasibility": 0.82 }, "confidence": "medium", "limitations": [ "Pelaporan realisasi RUED-P provinsi oleh Dinas ESDM ke DEN memiliki jeda publikasi 1-2 tahun antar-wilayah (laporan komparatif nasional terakhir Buku Bauran Energi DEN 2022)", "Sebagian provinsi mengalami kekosongan data historis karena keterlambatan penetapan Perda RUED (seperti Kaltim) atau terdampak fragmentasi administrasi pemekaran 4 DOB Papua", "Dokumen target Perda RUED umumnya menetapkan milestone 5 tahunan (2025/2050), sehingga memerlukan interpolasi linier target untuk panel tahunan kontinu", "Data belum terverifikasi melalui MCP; ketiadaan WebAPI resmi ESDM/DEN mengharuskan verifikasi berstatus partially-verified berbasis audit dokumen manual" ], "leakage_risks": [ "Jangan memasukkan target revisi RUED yang ditetapkan setelah tahun observasi berjalan" ], "decision": "screening", "decision_reason": "Relevansi kebijakan transisi energi tinggi, namun data realisasi EBT daerah berstatus partially-verified dengan reporting lag 1-2 tahun dan ketiadaan WebAPI; membutuhkan pipeline ekstraksi semi-otomatis dari dokumen Perda PDF DEN sebelum dipromosikan ke tahap eksperimen.", "project_slug": null }, { "schema_version": "1.0", "id": "cand-spatial-ipm-bottleneck", "title": "Pemodelan Spasial & Analisis Hambatan Kritis (Bottleneck) IPM 514 Kabupaten/Kota", "topic_id": "topic-human-capital-development", "provenance": { "acquisition_method": "bps_mcp", "source_type": "bps_mcp", "source_name": "BPS Indeks Pembangunan Manusia 514 Kab/Kota", "retrieved_at": "2026-03-05", "query_or_tool": "BPS MCP WebAPI Dimensi IPM (UHH, RLS, Pengeluaran Riil)", "verification_status": "verified" }, "status": "shortlisted", "problem_statement": "Peningkatan Indeks Pembangunan Manusia di tingkat kabupaten/kota sering terhambat oleh disparitas spasial dan ketidaktahuan pemda mengenai faktor pembatas utama (apakah kesehatan/UHH, lama sekolah, atau daya beli riil).", "signal_ids": [ "sig-ipm-district-gap" ], "potential_dataset_ids": [ "ds-bps-human-development-district-panel" ], "potential_target": "Indeks Pembangunan Manusia / IPM (Var ID 7) atau Klasifikasi Status IPM (Sangat Tinggi, Tinggi, Sedang, Rendah)", "potential_features": [ "Angka Harapan Hidup saat Lahir / UHH (Var ID 3)", "Rata-Rata Lama Sekolah / RLS (Var ID 5)", "Harapan Lama Sekolah / HLS (Var ID 4)", "Pengeluaran Riil per Kapita Disesuaikan (Var ID 6)" ], "scores": { "relevance": 0.9, "data_evidence": 0.95, "impact": 0.9, "data_quality": 0.9, "temporal_spatial_coverage": 0.95, "coverage": 0.95, "ml_potential": 0.85, "novelty": 0.75, "feasibility": 0.9 }, "confidence": "high", "limitations": [ "IPM adalah indeks komposit matematis sehingga pemodelan ML harus diarahkan pada analisis kontribusi spasial (Spatial Lag / GWR / SHAP) atau imputasi estimasi area kecil (SAE)" ], "leakage_risks": [ "Komponen penyusun IPM memiliki korelasi mekanis langsung dengan angka IPM sehingga analisis harus fokus pada dekomposisi bottleneck dan spasial spillover" ], "decision": "shortlisted", "decision_reason": "Ukuran sampel sangat besar (7.710 observasi panel = 514 daerah × 15 tahun), menjadikannya dataset paling komprehensif untuk analisis spasial di Indonesia.", "project_slug": null } ], "datasets": [ { "schema_version": "1.0", "id": "ds-bps-electricity-access-panel", "slug": "bps-electricity-access-panel", "name": "BPS Panel Akses & Kualitas Elektrifikasi Rumah Tangga", "description": "Panel data tahunan dan tri-tahunan mengenai sumber penerangan utama rumah tangga, ketersediaan listrik PLN vs non-PLN, dan infrastruktur penerangan jalan umum desa.", "domain": "infrastructure", "source_id": "src-bps", "provenance": { "acquisition_method": "bps_mcp", "source_type": "bps_mcp", "source_name": "Badan Pusat Statistik (BPS Indonesia)", "retrieved_at": "2026-09-13", "query_or_tool": "BPS Static Table 1555 & Podes 1759 via bps-statistics MCP", "verification_status": "verified" }, "geography": { "level": "Regency/City", "coverage": "514 Kabupaten/Kota & 34/38 Provinsi" }, "coverage": { "start": "2014", "end": "2024", "frequency": "Annual / Triennial" }, "granularity": "Kabupaten/Kota × Tahun", "sample_size": "514 Kabupaten/Kota × 10 Tahun ≈ 5.140 baris panel", "variables": [ { "name": "persentase_rt_listrik_pln_meteran", "type": "numeric", "role": "feature", "description": "Persentase rumah tangga dengan sumber penerangan listrik PLN menggunakan meteran mandiri (Susenas)", "unit": "%" }, { "name": "persentase_rt_listrik_pln_non_meteran", "type": "numeric", "role": "feature", "description": "Persentase rumah tangga dengan listrik PLN tanpa meteran mandiri / menyalur (Susenas)", "unit": "%" }, { "name": "persentase_rt_listrik_non_pln", "type": "numeric", "role": "target", "description": "Persentase rumah tangga menggunakan listrik non-PLN (genset swasta/komunal, turbin mikro)", "unit": "%" }, { "name": "persentase_rt_bukan_listrik", "type": "numeric", "role": "target", "description": "Persentase rumah tangga tanpa listrik / pelita / panel surya mandiri terbatas", "unit": "%" }, { "name": "desa_pengguna_listrik", "type": "numeric", "role": "feature", "description": "Jumlah desa/kelurahan menurut keberadaan keluarga pengguna listrik (Podes Tabel 1759)", "unit": "Desa" }, { "name": "persentase_penduduk_miskin_p0", "type": "numeric", "role": "feature", "description": "Persentase penduduk miskin P0 tingkat kabupaten/kota", "unit": "%" }, { "name": "pdrb_per_kapita_adhk", "type": "numeric", "role": "feature", "description": "PDRB per kapita atas dasar harga konstan 2010", "unit": "Juta Rupiah/Kapita" }, { "name": "topografi_keterisolasian_desa", "type": "numeric", "role": "feature", "description": "Rasio desa di daerah lereng/puncak atau kepulauan terpencil (Podes)", "unit": "%" }, { "name": "pdrb_kategori_d_share_provinsi_lag1", "type": "numeric", "role": "feature", "description": "Pangsa PDRB Kategori D (Pengadaan Listrik dan Gas) terhadap total PDRB provinsi tahun t-1 sebagai kontrol kontekstual makro anti-leakage", "unit": "%" } ], "data_quality": { "completeness": "Tinggi pada level kabupaten/kota Susenas Maret dan PDRB ADHK", "consistency": "Perbedaan interval pengumpulan: Susenas & PDRB tahunan kontinu, Podes tri-tahunan (2014, 2018, 2021, 2024)", "missingness": "Data Susenas/PDRB <3% missing; Data Podes memiliki missingness struktural 63.64% pada rentang panel 11 tahun (memerlukan interpolasi/forward-fill)", "known_issues": [ "Pemekaran wilayah DOB Papua (2022) diselaraskan ke baseline 34 provinsi/514 kabupaten", "Survei Podes dilaksanakan dalam siklus 3 tahunan (2014, 2018, 2021, 2024)", "Variabel fisik jarak ke gardu induk tidak tersedia di data publik; diproksikan melalui rasio penerangan jalan umum desa (Podes)" ] }, "limitations": [ "Interpolasi Podes antar-gelombang harus diuji kekuatannya (robustness check) terhadap model 4-gelombang murni" ], "constraints": [ "Susenas modul konsumsi dan kesejahteraan dirilis tahunan pada semester kedua" ] }, { "schema_version": "1.0", "id": "ds-bps-electricity-consumption-generation", "slug": "bps-electricity-consumption-generation", "name": "BPS Runtun Waktu Pembangkitan & Penjualan Listrik Sektoral", "description": "Data statistik ketenagalistrikan mencakup kapasitas terpasang pembangkit, produksi bruto/neto, pembelian dari IPP, dan volume penjualan tenaga listrik per golongan tarif (Industri, Rumah Tangga, Bisnis, Publik) serta captive power industri.", "domain": "infrastructure", "source_id": "src-bps", "provenance": { "acquisition_method": "bps_mcp", "source_type": "bps_mcp", "source_name": "Badan Pusat Statistik (BPS Indonesia)", "retrieved_at": "2026-09-13", "query_or_tool": "Publikasi BPS Statistik Listrik 2020-2024 via bps-statistics MCP", "verification_status": "verified" }, "geography": { "level": "Province", "coverage": "34 Provinsi & Wilayah Distribusi PLN" }, "coverage": { "start": "2010", "end": "2024", "frequency": "Quarterly / Annual" }, "granularity": "Provinsi / Wilayah Distribusi × Tahun / Triwulan", "sample_size": "34 Provinsi × 15 Tahun ≈ 510 baris observasi tahunan", "variables": [ { "name": "penjualan_listrik_industri", "type": "numeric", "role": "feature", "description": "Volume penjualan tenaga listrik PLN kelompok tarif industri I1-I4 (MWh)", "unit": "MWh" }, { "name": "penjualan_listrik_rumah_tangga", "type": "numeric", "role": "feature", "description": "Volume penjualan tenaga listrik PLN kelompok tarif rumah tangga R1-R3 (MWh)", "unit": "MWh" }, { "name": "penjualan_listrik_bisnis", "type": "numeric", "role": "feature", "description": "Volume penjualan tenaga listrik PLN kelompok tarif bisnis B1-B3 (MWh)", "unit": "MWh" }, { "name": "kapasitas_terpasang_pembangkit", "type": "numeric", "role": "feature", "description": "Daya terpasang pembangkit tenaga listrik PLN dan non-PLN (MW)", "unit": "MW" }, { "name": "produksi_listrik_bruto", "type": "numeric", "role": "feature", "description": "Total energi listrik yang dibangkitkan (GWh)", "unit": "GWh" }, { "name": "susut_jaringan_transmisi_distribusi", "type": "numeric", "role": "feature", "description": "Susut tenaga listrik dalam jaringan transmisi dan distribusi (GWh / %)", "unit": "%" }, { "name": "captive_power_manufaktur", "type": "numeric", "role": "feature", "description": "Daya dan produksi listrik dari pembangkit mandiri industri manufaktur IBS (kWh / kVA)", "unit": "kVA" }, { "name": "pertumbuhan_pdrb_manufaktur_triwulanan", "type": "numeric", "role": "target", "description": "Laju pertumbuhan PDRB sektor industri pengolahan triwulanan ADHK 2010", "unit": "%" } ], "data_quality": { "missingness": "Data runtun waktu nasional dan wilayah kerja PLN relatif lengkap", "known_issues": [ "Sebagian data historis dikelompokkan berdasarkan Unit Induk Wilayah (UIW) PLN yang mencakup multi-provinsi", "Survei Captive Power BPS diterbitkan secara reguler sejak 2014" ] }, "constraints": [ "Publikasi tahunan rilis pada akhir tahun berikutnya (T+1)" ] }, { "schema_version": "1.0", "id": "ds-bps-food-security-inflation-monthly", "slug": "bps-food-security-inflation-monthly", "name": "BPS Runtun Waktu Bulanan Ketahanan Pangan, NTP & Inflasi", "description": "Dataset runtun waktu bulanan yang menghubungkan indikator harga produsen pertanian (NTP, It, Ib, KSA produksi padi) dengan indikator harga konsumen (IHK 90 Kota dan Inflasi Makanan).", "domain": "agriculture", "source_id": "src-bps", "provenance": { "acquisition_method": "bps_mcp", "source_type": "bps_mcp", "source_name": "Badan Pusat Statistik (BPS Indonesia)", "retrieved_at": "2026-03-05", "query_or_tool": "BPS WebAPI Subject 3 / 1498 / Var 1 via bps-statistics MCP", "verification_status": "verified" }, "geography": { "level": "Province / City", "coverage": "34 Provinsi Sentra Pertanian & 90 Kota Pemantauan IHK" }, "coverage": { "start": "2018-01", "end": "2024-12", "frequency": "Monthly" }, "granularity": "Provinsi / Kota IHK × Bulan observasi", "sample_size": "34 Provinsi × 84 Bulan = 2.856 baris waktu bulanan", "variables": [ { "name": "inflasi_kelompok_makanan", "type": "numeric", "role": "target", "description": "Inflasi Kelompok Makanan, Minuman, dan Tembakau MoM / YoY (Var ID 1890)", "unit": "%" }, { "name": "luas_panen_produksi_padi", "type": "numeric", "role": "target", "description": "Luas Panen, Produksi, dan Produktivitas Padi KSA (Var ID 1498 / Var ID 23)", "unit": "Hektar / Ton / Ku/Ha" }, { "name": "nilai_tukar_petani_ntp", "type": "numeric", "role": "feature", "description": "Nilai Tukar Petani Gabungan menurut Provinsi (Var ID 10)", "unit": "Indeks (Tahun Dasar)" }, { "name": "nilai_tukar_petani_tanaman_pangan_ntpp", "type": "numeric", "role": "feature", "description": "Nilai Tukar Petani Tanaman Pangan (Var ID 14)", "unit": "Indeks (Tahun Dasar)" }, { "name": "indeks_harga_diterima_petani_it", "type": "numeric", "role": "feature", "description": "Indeks Harga yang Diterima Petani (Var ID 11)", "unit": "Indeks" }, { "name": "indeks_harga_dibayar_petani_ib", "type": "numeric", "role": "feature", "description": "Indeks Harga yang Dibayar Petani (Var ID 12)", "unit": "Indeks" }, { "name": "inflasi_umum_bulanan", "type": "numeric", "role": "feature", "description": "Inflasi Umum Bulanan M-to-M (Var ID 1)", "unit": "%" }, { "name": "indeks_harga_konsumen_ihk", "type": "numeric", "role": "feature", "description": "Indeks Harga Konsumen 90 Kota (Var ID 1709)", "unit": "Indeks" } ], "data_quality": { "missingness": "Data lengkap 2018–2024 untuk 90 kota IHK dan 34 provinsi NTP", "known_issues": [ "Perubahan tahun dasar IHK dari 2018=100 ke 2022=100 pada rilis awal 2024", "Metode KSA padi diimplementasikan secara resmi sejak 2018" ] }, "constraints": [ "Rilis bulanan setiap awal bulan (hari kerja pertama BPS)" ] }, { "schema_version": "1.0", "id": "ds-bps-human-development-district-panel", "slug": "bps-human-development-district-panel", "name": "BPS Panel Indeks Pembangunan Manusia 514 Kabupaten/Kota", "description": "Panel data tahunan Indeks Pembangunan Manusia (IPM) beserta 3 dimensi penyusunnya (kesehatan/UHH, pendidikan/RLS-HLS, standar hidup layak/pengeluaran riil) pada 514 kabupaten/kota se-Indonesia.", "domain": "social", "source_id": "src-bps", "provenance": { "acquisition_method": "bps_mcp", "source_type": "bps_mcp", "source_name": "Badan Pusat Statistik (BPS Indonesia)", "retrieved_at": "2026-03-05", "query_or_tool": "BPS Indeks Pembangunan Manusia 514 Kab/Kota via bps-statistics MCP", "verification_status": "verified" }, "geography": { "level": "Regency/City", "coverage": "514 Kabupaten/Kota" }, "coverage": { "start": "2010", "end": "2024", "frequency": "Annual" }, "granularity": "514 Kabupaten/Kota × Tahun", "sample_size": "514 Kabupaten/Kota × 15 Tahun = 7.710 observasi panel", "variables": [ { "name": "indeks_pembangunan_manusia_ipm", "type": "numeric", "role": "target", "description": "Indeks Pembangunan Manusia (IPM) Menurut Kabupaten/Kota (Var ID 7)", "unit": "Indeks (0-100)" }, { "name": "angka_harapan_hidup_saat_lahir", "type": "numeric", "role": "feature", "description": "Angka Harapan Hidup saat Lahir (Dimensi Kesehatan) (Var ID 3)", "unit": "Tahun" }, { "name": "rata_rata_lama_sekolah", "type": "numeric", "role": "feature", "description": "Rata-Rata Lama Sekolah Penduduk Usia 25+ (Var ID 5)", "unit": "Tahun" }, { "name": "harapan_lama_sekolah", "type": "numeric", "role": "feature", "description": "Harapan Lama Sekolah Penduduk Usia 7+ (Var ID 4)", "unit": "Tahun" }, { "name": "pengeluaran_per_kapita_disesuaikan", "type": "numeric", "role": "feature", "description": "Pengeluaran Riil per Kapita Disesuaikan (Dimensi Standar Hidup Layak) (Var ID 6)", "unit": "Ribu Rupiah/Tahun" } ], "data_quality": { "missingness": "Data lengkap 514 Kabupaten/Kota periode 2010–2024 (Metode Baru Seri 2010)", "known_issues": [ "Kabupaten baru hasil pemekaran sebelum 2014 memiliki data yang dihitung secara retrospektif oleh BPS" ] }, "constraints": [ "Rilis IPM tahunan dilakukan pada bulan November/Desember setiap tahun" ] }, { "schema_version": "1.0", "id": "ds-bps-pdrb-structural-transformation", "slug": "bps-pdrb-structural-transformation", "name": "BPS Panel PDRB, Produktivitas Sektoral & Ketenagakerjaan", "description": "Panel data triwulanan dan tahunan PDRB ADHK 2010 menurut 17 lapangan usaha, pertumbuhan ekonomi, PDRB per kapita, dan penyerapan tenaga kerja regional.", "domain": "economy", "source_id": "src-bps", "provenance": { "acquisition_method": "bps_mcp", "source_type": "bps_mcp", "source_name": "Badan Pusat Statistik (BPS Indonesia)", "retrieved_at": "2026-03-05", "query_or_tool": "BPS PDRB ADHK 2010 Sektoral & Sakernas via bps-statistics MCP", "verification_status": "verified" }, "geography": { "level": "Province", "coverage": "34/38 Provinsi" }, "coverage": { "start": "2010", "end": "2024", "frequency": "Quarterly / Annual" }, "granularity": "Provinsi × Triwulan (Q1–Q4) / Tahun", "sample_size": "34 Provinsi × 60 Triwulan ≈ 2.040 observasi panel triwulanan", "variables": [ { "name": "laju_pertumbuhan_pdrb_adhk", "type": "numeric", "role": "target", "description": "Laju Pertumbuhan PDRB ADHK 2010 Menurut Provinsi (Var ID 291)", "unit": "%" }, { "name": "pdrb_adhk_sektoral", "type": "numeric", "role": "feature", "description": "PDRB Sektor Industri Pengolahan, Pertanian, Perdagangan, Konstruksi (Var ID 286)", "unit": "Miliar Rupiah" }, { "name": "pdrb_per_kapita", "type": "numeric", "role": "feature", "description": "PDRB ADHB / ADHK Per Kapita menurut Provinsi (Var ID 288)", "unit": "Juta Rupiah/Kapita" }, { "name": "distribusi_pdrb_daerah", "type": "numeric", "role": "feature", "description": "Distribusi Persentase PDRB Daerah terhadap PDRB Nasional (Var ID 289)", "unit": "%" }, { "name": "penyerapan_tenaga_kerja_sektoral", "type": "numeric", "role": "feature", "description": "Penyerapan Tenaga Kerja per Lapangan Usaha Sakernas (Var ID 520)", "unit": "Orang / %" }, { "name": "tingkat_pengangguran_terbuka", "type": "numeric", "role": "feature", "description": "Tingkat Pengangguran Terbuka Sakernas (Var ID 543)", "unit": "%" }, { "name": "nilai_ekspor_impor_daerah", "type": "numeric", "role": "feature", "description": "Nilai Ekspor dan Impor Daerah (Var ID 8)", "unit": "Juta USD" }, { "name": "pdrb_manufaktur_adhk_triwulanan", "type": "numeric", "role": "target_candidate", "description": "PDRB ADHK 2010 Kategori C Industri Pengolahan Triwulanan Menurut Provinsi (Var ID 2267)", "unit": "Miliar Rupiah" }, { "name": "ekspor_nonmigas_bulanan_provinsi", "type": "numeric", "role": "feature_candidate", "description": "Nilai Ekspor Nonmigas Bulanan Menurut Provinsi Asal Barang (Var ID 2346) - Proxy aktivitas industri pengolahan daerah", "unit": "Ribu US$" }, { "name": "indeks_produksi_imk_triwulanan", "type": "numeric", "role": "feature_candidate", "description": "Indeks Produksi Triwulanan Industri Skala Mikro dan Kecil Menurut Provinsi (Var ID 401)", "unit": "Indeks (2010=100)" }, { "name": "indeks_produksi_ibs_nasional", "type": "numeric", "role": "feature_candidate", "description": "Indeks Produksi Triwulanan IBS Nasional (Var ID 89 - Variabel Kontrol Makro)", "unit": "Indeks (2010=100)" } ], "data_quality": { "missingness": "Data PDRB ADHK 2010 konsisten sejak rilis tahun dasar 2010; Var 2346 missingness 0% pada 34-38 provinsi (2022-2026); Var 401 kontinu (2016-2025)", "known_issues": [ "Dampak pandemi COVID-19 pada 2020 menciptakan diskontinuitas struktural", "Var 2346 merupakan proxy perdagangan luar negeri yang memuat porsi komoditas ekstraktif di provinsi tambang (Kaltim/Kalsel)", "Nilai rilis awal Var 2346 mengalami revisi rutin ke bawah (-0,40% s.d. -13,84%) seiring penyelesaian dokumen PEB susulan" ] }, "constraints": [ "Publikasi PDRB triwulanan dirilis sekitar 5–6 minggu setelah akhir triwulan (hari kerja pertama bulan kedua pasca-kuartal, misal 6 Mei 2024 untuk Q1 2024)", "Rilis bulanan ekspor terbit sekitar pertengahan bulan berikutnya berdasarkan kalender BRS aktual (misal: 22 April 2024 untuk Maret 2024, lead time 14 hari)", "Evaluasi pseudo-out-of-sample wajib menggunakan first-release vintages dari dokumen BRS kontemporer, bukan data current revised API", "Var 2346 dan Var 401 berstatus CONDITIONAL, dan target Var 2267 terverifikasi pada level sampel vintage; seluruh pemodelan empiris tetap GATED sampai basis data vintage historis BRS lengkap direkonstruksi" ] }, { "schema_version": "1.0", "id": "ds-bps-poverty-vulnerability-panel", "slug": "bps-poverty-vulnerability-panel", "name": "BPS Panel Sosio-Ekonomi, Kemiskinan & Ketenagakerjaan", "description": "Panel data tahunan/semesteran variabel kemiskinan, ketimpangan pengeluaran, ketenagakerjaan, dan standar hidup layak antar-provinsi dan kabupaten/kota dari Susenas dan Sakernas.", "domain": "social", "source_id": "src-bps", "provenance": { "acquisition_method": "bps_mcp", "source_type": "bps_mcp", "source_name": "Badan Pusat Statistik (BPS Indonesia)", "retrieved_at": "2026-03-05", "query_or_tool": "BPS Susenas Maret-September & Gini Ratio via bps-statistics MCP", "verification_status": "verified" }, "geography": { "level": "Province / Regency-City", "coverage": "34 Provinsi / 514 Kabupaten-Kota" }, "coverage": { "start": "2010", "end": "2024", "frequency": "Semi-annual / Annual" }, "granularity": "Provinsi / Kab-Kota × Periode Semesteran (Maret & September)", "sample_size": "34 Provinsi × 15 Tahun ≈ 510 baris (Provinsi) atau ≈ 7.700 baris (Kab/Kota)", "variables": [ { "name": "persentase_penduduk_miskin_p0", "type": "numeric", "role": "target", "description": "Persentase Penduduk Miskin (P0) menurut Daerah (Var ID 184)", "unit": "%" }, { "name": "jumlah_penduduk_miskin", "type": "numeric", "role": "target", "description": "Jumlah Penduduk Miskin (Var ID 183)", "unit": "Ribu/Juta Jiwa" }, { "name": "gini_ratio", "type": "numeric", "role": "feature", "description": "Gini Ratio Menurut Provinsi dan Daerah (Var ID 98)", "unit": "Rasio (0-1)" }, { "name": "garis_kemiskinan", "type": "numeric", "role": "feature", "description": "Garis Kemiskinan Makanan & Non-Makanan (Var ID 182)", "unit": "Rupiah/Kapita/Bulan" }, { "name": "tingkat_pengangguran_terbuka_tpt", "type": "numeric", "role": "feature", "description": "Tingkat Pengangguran Terbuka (TPT) Sakernas (Var ID 543)", "unit": "%" }, { "name": "pengeluaran_per_kapita_disesuaikan", "type": "numeric", "role": "feature", "description": "Pengeluaran Riil per Kapita Disesuaikan (Var ID 6)", "unit": "Ribu Rupiah/Tahun" }, { "name": "rata_rata_lama_sekolah_rls", "type": "numeric", "role": "feature", "description": "Rata-Rata Lama Sekolah Penduduk Usia 25+ (Var ID 5)", "unit": "Tahun" }, { "name": "angka_harapan_hidup_uhh", "type": "numeric", "role": "feature", "description": "Angka Harapan Hidup saat Lahir (Var ID 3)", "unit": "Tahun" } ], "data_quality": { "missingness": "Data lengkap pada agregasi provinsi 2010–2024; beberapa kabupaten pemekaran baru diimputasi ke data induk", "known_issues": [ "Pemekaran 4 provinsi baru di Papua pada tahun 2022 memerlukan penyelarasan batas wilayah baseline 34 provinsi" ] }, "constraints": [ "Survei Susenas dilaksanakan dua kali setahun (Maret dan September)" ] }, { "schema_version": "1.0", "id": "ds-esdm-ebt-regional-balance", "slug": "esdm-ebt-regional-balance", "name": "ESDM & DEN Neraca Potensi dan Realisasi EBT Daerah", "description": "Kompilasi data sektoral capaian bauran energi baru terbarukan (EBT), kapasitas terpasang pembangkit EBT (PLTS, PLTA, PLTP, Biomassa), dan evaluasi target Rencana Umum Energi Daerah Provinsi (RUED-P).", "domain": "infrastructure", "source_id": "src-esdm", "provenance": { "acquisition_method": "file", "source_type": "file", "source_name": "Kementerian ESDM & Dewan Energi Nasional (DEN)", "retrieved_at": "2026-09-13", "query_or_tool": "Audit dokumen fisik PDF Buku Bauran Energi DEN 2022 & Laporan HEESI ESDM", "verification_status": "partially-verified" }, "geography": { "level": "Province", "coverage": "34 Provinsi" }, "coverage": { "start": "2015", "end": "2024", "frequency": "Annual" }, "granularity": "Provinsi × Tahun", "sample_size": "34 Provinsi × 10 Tahun = 340 baris observasi", "variables": [ { "name": "persentase_bauran_ebt_daerah", "type": "numeric", "role": "target", "description": "Realisasi persentase bauran energi baru terbarukan terhadap total bauran energi primer daerah", "unit": "%" }, { "name": "target_bauran_ebt_rued", "type": "numeric", "role": "feature", "description": "Target persentase bauran EBT dalam dokumen perda RUED-P provinsi", "unit": "%" }, { "name": "kapasitas_terpasang_plts", "type": "numeric", "role": "feature", "description": "Kapasitas terpasang pembangkit listrik tenaga surya (MWp)", "unit": "MWp" }, { "name": "kapasitas_terpasang_plta_pltmh", "type": "numeric", "role": "feature", "description": "Kapasitas terpasang PLTA dan PLTMH tenaga air (MW)", "unit": "MW" }, { "name": "kapasitas_terpasang_plt_biomassa", "type": "numeric", "role": "feature", "description": "Kapasitas terpasang pembangkit listrik tenaga biomassa dan biogas (MW)", "unit": "MW" }, { "name": "kapasitas_fiskal_daerah", "type": "numeric", "role": "feature", "description": "Indeks kapasitas fiskal atau rasio pendapatan asli daerah terhadap total APBD", "unit": "Rasio" }, { "name": "potensi_teknis_surya_daerah", "type": "numeric", "role": "feature", "description": "Potensi teknis energi surya berbasis radiasi harian rata-rata (kWh/m2/hari)", "unit": "kWh/m2/hari" } ], "data_quality": { "completeness": "Sebagian (partially-complete); sekitar 30 provinsi telah mengesahkan Perda RUED-P, namun data capaian kontinu 2015-2024 tidak lengkap di seluruh daerah", "consistency": "Terdapat perbedaan perlakuan biomassa tradisional (kayu bakar) antar-Dinas ESDM daerah serta perubahan standar SEEA pada Neraca Energi BPS sejak 2020", "missingness": "Data panel tahunan mengalami kekosongan di provinsi yang terlambat mengesahkan Perda RUED (seperti Kaltim) atau terdampak pemekaran 4 DOB Papua", "known_issues": [ "Pelaporan realisasi capaian RUED-P provinsi oleh Dinas ESDM ke DEN mengalami jeda publikasi (reporting lag) 1-2 tahun (laporan nasional komparatif terakhir tahun 2022)", "Target RUED-P dalam dokumen Perda berformat interval 5 tahunan (milestone 2025/2050), memerlukan interpolasi linier untuk target tahunan kontinu", "Tidak tersedia public WebAPI dari Kementerian ESDM maupun DEN; data bersumber dari ekstraksi manual/semi-otomatis dokumen laporan HEESI dan Perda RUED-P DEN" ] }, "limitations": [ "Data belum terverifikasi melalui MCP/API resmi; verifikasi berstatus partially-verified berbasis audit dokumen fisik PDF pemerintah", "Pemekaran 4 DOB di Papua pada akhir 2022 memerlukan agregasi balik ke Papua & Papua Barat untuk menjaga konsistensi 34 provinsi baseline" ], "constraints": [ "Data bersumber dari kompilasi publikasi tahunan HEESI Kementerian ESDM, Buku Bauran Energi Nasional DEN, dan dokumen Perda RUED Provinsi" ] } ], "literature": [ { "schema_version": "1.0", "id": "lit-burke-2019-indonesia-electricity", "record_type": "canonical", "slug": "burke-2019-indonesia-electricity", "title": "Indonesian Electricity Sector Decarbonisation: Pathways, Barriers, and Policy Choices", "authors": [ "Paul J. Burke", "Saleh Abdurrahman" ], "publication_year": 2019, "publication_type": "journal-article", "journal_or_venue": "Energy Policy", "volume": "131", "pages": "388-397", "publisher": "Elsevier", "doi": "10.1016/j.enpol.2019.04.034", "url": "https://doi.org/10.1016/j.enpol.2019.04.034", "abstract": "Indonesia faces crucial challenges in decarbonising its electricity sector given heavy coal dependency and rapid demand growth. This study evaluates structural bottlenecks, regulatory hurdles, captive power expansion in industrial estates, and policy opportunities for integrating renewable generation into the national grid.", "keywords": [ "Indonesia", "electricity decarbonisation", "renewable energy", "coal power", "captive generation", "energy policy" ], "source_id": "src-scholarly-repository", "citation": "Burke, P. J., & Abdurrahman, S. (2019). Indonesian electricity sector decarbonisation: Pathways, barriers, and policy choices. Energy Policy, 131, 388-397. https://doi.org/10.1016/j.enpol.2019.04.034", "provenance": { "acquisition_method": "web", "source_type": "web", "source_classification": "scholarly", "source_name": "Energy Policy Journal (Elsevier)", "retrieved_at": "2026-09-14", "query_or_tool": "DOI resolver / Crossref metadata audit", "verification_status": "verified" }, "verification_status": "partially-verified", "verification_details": { "metadata_verified": true, "content_verified": false, "research_interpretation_verified": false, "verified_by": "Solo Researcher", "verified_at": "2026-09-14", "notes": "Metadata verified via Crossref DOI resolution. Content not independently verified against real PDF artifact (previous document artifact was a dummy fixture and has been removed). Full-text content verification requires a real PDF." }, "research_context": "Evaluates macro policy choices and industrial grid integration challenges in Indonesia's power sector (provisional synthesis from published abstract and metadata; primary text unverified).", "methods_summary": "Semi-structured policy analysis, sectoral historical trends, and electricity balance review.", "data_summary": "National PLN electricity balance, MEMR ESDM statistics, and industrial energy reports.", "findings_summary": "Identified high growth in off-grid captive coal capacity as a major risk factor slowing down grid-level decarbonisation commitments.", "limitations_summary": "Analysis conducted primarily at national level; lacks granular district-level panel data on captive power.", "relevance_notes": "Provides provisional literature context on the captive power barrier for candidate cand-captive-power-industrial-transition; full-text validation pending primary PDF acquisition.", "literature_analysis": { "research_question": "What are the primary institutional, financial, and technical barriers to decarbonising Indonesia's electricity sector?", "study_design": "Qualitative and quantitative policy synthesis of national electricity data", "methodology": "Techno-economic and policy barrier analysis", "population_or_unit": "National electricity sector & industrial clusters", "geography": "Indonesia (National)", "data_sources": [ "PLN Statistics", "ESDM Handbook of Energy & Economic Statistics of Indonesia" ], "key_findings": [ "Coal expansion lock-in and captive power agreements reduce incentives for grid renewable penetration.", "Regional grid overcapacity in Java-Bali coexists with reliability deficits in off-Java regions." ], "limitations": [ "Does not model individual firm-level switching behavior across manufacturing subsectors." ], "research_gap": { "established": "Macro-level policies and power purchase agreements hinder rapid renewable transition in Indonesia.", "uncertain": "Extent to which industrial manufacturing plants are willing or able to retire captive fossil generation given reliability constraints.", "geographic_gap": "Lacks subnational district-level econometric modeling across Outer Island industrial corridors.", "temporal_gap": "Covers data up to 2018; misses post-2020 RUED implementation and recent nickel smelter captive boom.", "data_gap": "Did not leverage BPS Large and Medium Industrial (IBS) microdata or Podes village electrification quality surveys.", "methodological_gap": "Relied on descriptive sectoral analysis rather than causal or machine-learning nowcasting models.", "proposed_contribution": "Research OS candidate cand-captive-power-industrial-transition models firm-level captive power probabilities using BPS IBS and PLN regional statistics." }, "relevance_to_candidate": [ "cand-captive-power-industrial-transition" ] } }, { "schema_version": "1.0", "id": "lit-chojkiewicz-2025-solar-storage-captive", "record_type": "canonical", "slug": "chojkiewicz-2025-solar-storage-captive", "title": "Declining costs make solar plus storage economical for industrial captive power", "authors": [ "Emilia Chojkiewicz", "Nikit Abhyankar", "Umed Paliwal", "Amol Phadke" ], "publication_year": 2025, "publication_type": "journal-article", "journal_or_venue": "iScience", "volume": "28", "issue": "11", "pages": "113763", "publisher": "Elsevier", "doi": "10.1016/j.isci.2025.113763", "url": "https://doi.org/10.1016/j.isci.2025.113763", "abstract": "Significant new coal-fired captive power generation is planned globally to support industrial applications. This is particularly true in Indonesia, where tens of GW of captive coal are in development to support metal processing at least in part for the manufacture of clean technologies such as batteries. However, recent cost declines in renewables and battery storage, along with performance improvements in battery cycle life, energy density, and critical-mineral intensity, have opened up new opportunities for economical electricity generation across the country. Here we assess the rapidly growing region of Kalimantan and show how, with targeted support policies, the co-location of solar PV generation with battery storage can achieve a Levelized Cost of Energy (LCOE) of 5.6–7.9 cents/kWh at present, varying with capacity factor and financing conditions, competitive with conventional captive coal generation for industrial applications. With a supportive policy and regulatory framework, the reduction of existing coal subsidies, and preferential financing terms, solar+storage can offer GW-scale potential as an economical alternative to new captive power plants, with a minimal land footprint, in Indonesia and other emerging economies.", "keywords": [ "Industrial captive power", "Solar PV", "Battery energy storage", "Captive coal", "Kalimantan", "Levelized cost of energy", "Indonesia" ], "source_id": "src-scholarly-repository", "citation": "Chojkiewicz, E., Abhyankar, N., Paliwal, U., & Phadke, A. (2025). Declining costs make solar plus storage economical for industrial captive power. iScience, 28(11), 113763. https://doi.org/10.1016/j.isci.2025.113763", "document_ids": [ "doc-chojkiewicz-2025-solar-storage-captive" ], "provenance": { "acquisition_method": "file", "source_classification": "scholarly", "source_name": "iScience (Elsevier Open Access)", "retrieved_at": "2026-09-16", "query_or_tool": "Direct PDF inspection and text extraction from documents/pdf/chojkiewicz-et-al-2025.pdf", "verification_status": "verified" }, "verification_status": "verified", "verification_details": { "metadata_verified": true, "content_verified": true, "research_interpretation_verified": false, "verified_by": "Solo Researcher", "verified_at": "2026-09-16", "notes": "Primary PDF binary inspected and full text extracted. Verified Indonesian captive coal context (11 GW in 2023, 14 GW proposed/in development), Kalimantan case study, solar+storage LCOE 5.6-7.9 c/kWh, 0.1% land footprint for 4-6 GW fossil replacement. Techno-economic model, not econometric causal study." }, "research_context": "Evaluates techno-economic feasibility and system design of replacing planned industrial coal-fired captive power plants with solar PV plus battery energy storage in Kalimantan, Indonesia.", "methods_summary": "Techno-economic modeling, hourly solar resource and dispatch simulation, and levelized cost of energy (LCOE) sensitivity analysis under varying financing conditions, capacity factors, and subsidy structures.", "data_summary": "Hourly solar irradiance data from ERA5/NSRDB, battery performance degradation models, balance-of-system cost projections, global and Indonesian captive coal capital and fuel cost estimates.", "findings_summary": "Solar PV co-located with battery storage achieves an LCOE of 5.6–7.9 cents/kWh in Kalimantan, becoming cost-competitive with new captive coal. Co-location cuts storage balance-of-system and interconnection costs by up to 20%. Dedicating approximately 0.1% of Kalimantan's land area to solar+storage could substitute for 4–6 GW of planned industrial captive fossil generation.", "limitations_summary": "Techno-economic engineering simulation rather than econometric analysis of firm adoption behavior. Does not model firm decision-making, grid interconnection contractual barriers, or micro-level firm data.", "relevance_notes": "Provides vital electrical engineering and energy transition context for cand-captive-power-industrial-transition, proving that captive power is an engineering and supply-side choice with viable renewable alternatives, while highlighting the need for empirical firm-level adoption research.", "literature_analysis": { "research_question": "Can solar PV combined with battery energy storage economically substitute for planned coal-fired captive power plants in Indonesia's industrial corridors?", "study_design": "Techno-economic simulation and cost optimization model", "methodology": "Hourly dispatch simulation, LCOE modeling, sensitivity analysis on capital costs and discount rates", "population_or_unit": "Industrial captive power systems / regional industrial estates", "geography": "Kalimantan, Indonesia", "data_sources": [ "Global captive power databases", "ERA5 / NSRDB hourly solar irradiance", "Battery pack and inverter cost benchmark databases" ], "key_findings": [ "Indonesian captive coal capacity expanded 8-fold over the past decade to 11 GW in 2023, with an additional 14 GW planned or under construction.", "Solar PV plus battery storage achieves LCOE of 5.6–7.9 cents/kWh under current conditions, competitive with captive coal.", "Co-locating storage with solar reduces balance-of-system costs by up to 20% compared to standalone deployment.", "Utilizing 0.1% of Kalimantan land area could replace 4–6 GW of industrial captive fossil capacity." ], "limitations": [ "Does not evaluate empirical firm switching determinants or econometrically estimate firm adoption probabilities.", "Focuses primarily on Kalimantan's solar resource and mineral processing context; does not model Java or Sumatra industrial clusters." ], "research_gap": { "established": "Techno-economically, solar plus storage can achieve parity with industrial captive coal in Indonesia under supportive regulatory and financing conditions.", "uncertain": "Actual empirical adoption rates, grid-interconnection willingness, and firm-level constraints across diverse manufacturing subsectors.", "geographic_gap": "Focuses on Kalimantan; does not examine provincial heterogeneity across Sulawesi, North Maluku, or Java.", "temporal_gap": "Projected 2024–2030 model benchmarks; does not provide historical longitudinal tracking of plant-by-plant captive additions.", "data_gap": "Does not link to official BPS manufacturing census microdata (IBS) or PLN regional feeder reliability metrics.", "methodological_gap": "Engineering simulation and optimization rather than microeconometric or machine learning classification of firm decisions.", "proposed_contribution": "Research OS candidate cand-captive-power-industrial-transition complements this techno-economic feasibility benchmark by providing micro-level empirical modeling of firm captive adoption determinants in Indonesia." }, "relevance_to_candidate": [ "cand-captive-power-industrial-transition" ] } }, { "schema_version": "1.0", "id": "lit-kassem-2024-electrification-industrial-development", "record_type": "canonical", "slug": "kassem-2024-electrification-industrial-development", "title": "Does electrification cause industrial development? Grid expansion and firm turnover in Indonesia", "authors": [ "Dana Kassem" ], "publication_year": 2024, "publication_type": "journal-article", "journal_or_venue": "Journal of Development Economics", "volume": "167", "pages": "103234", "publisher": "Elsevier", "doi": "10.1016/j.jdeveco.2023.103234", "url": "https://doi.org/10.1016/j.jdeveco.2023.103234", "abstract": "I ask whether electrification causes industrial development. I combine newly digitized data from the Indonesian state electricity company with rich manufacturing census data. To understand how electrification can cause industrial development, I shed light on an important economic mechanism — firm turnover. In particular, I study the effect of the extensive margin of electrification (grid expansion) on the extensive margin of industrial development (firm entry and exit). To deal with endogenous grid placement, I use an instrumental variable approach exploiting the location of colonial electric infrastructure and the need for an interconnected grid on the island of Java. I find that electrification causes industrial development by increasing the number of manufacturing firms, manufacturing workers, and manufacturing output. Electrification increases firm entry rates, but also exit rates, and entry accounts for most of the increase in output. This is consistent with electrification lowering entry costs, increasing competition, and forcing unproductive firms to exit more often.", "keywords": [ "Electrification", "Grid expansion", "Industrial development", "Firm turnover", "Manufacturing census", "Instrumental variables", "Indonesia", "Java" ], "source_id": "src-scholarly-repository", "citation": "Kassem, D. (2024). Does electrification cause industrial development? Grid expansion and firm turnover in Indonesia. Journal of Development Economics, 167, 103234. https://doi.org/10.1016/j.jdeveco.2023.103234", "document_ids": [], "provenance": { "acquisition_method": "web", "source_classification": "scholarly", "source_name": "Journal of Development Economics (Elsevier) & IGC Working Paper Series", "retrieved_at": "2026-09-16", "query_or_tool": "DOI resolver, Crossref metadata audit, ScienceDirect preview, and IGC / VoxDev research summaries", "verification_status": "partially-verified" }, "verification_status": "partially-verified", "verification_details": { "metadata_verified": true, "content_verified": false, "research_interpretation_verified": false, "verified_by": "Solo Researcher", "verified_at": "2026-09-16", "notes": "Metadata verified via Crossref and ScienceDirect catalog. Substantive causal mechanisms confirmed via publisher abstract and author working papers (IGC / VoxDev / CRC TR 224). Full primary journal article PDF not locally archived. Epistemic role: rigorous causal evidence on grid expansion and manufacturing growth in Java; not a nowcasting paper." }, "research_context": "Investigates the causal impact of extensive-margin electricity grid expansion on manufacturing growth, firm turnover, and productivity in Java, Indonesia (1990–2000).", "methods_summary": "Panel instrumental variables (IV) estimation exploiting historical colonial-era electrical infrastructure and network routing topology to address endogenous grid placement across 24,824 villages (desas).", "data_summary": "Digitized historical PLN transmission grid maps and substation locations merged with BPS Annual Manufacturing Census (Survei Industri / IBS) microdata covering 1990–2000 across 24,824 desas in Java.", "findings_summary": "Electrification causes significant industrial growth by increasing manufacturing plant counts, employment, and output. Firm turnover is the dominant economic channel: grid connection lowers operational entry barriers and increases competitive pressure, leading to higher entry rates of productive firms and higher exit rates of unproductive incumbents.", "limitations_summary": "Focuses on historical grid electrification in Java (1990–2000) during rapid rural grid roll-out. Does not directly evaluate modern high-frequency sales nowcasting or post-2020 off-grid industrial captive power expansion outside Java.", "relevance_notes": "Provides essential structural and causal foundation for the Indonesia electricity-industry research program. Proves that electricity infrastructure has a profound causal relationship with manufacturing activity in Indonesia, while cautioning against conflating historical long-run causal grid expansion with short-run quarterly nowcasting.", "literature_analysis": { "research_question": "Does electricity grid expansion cause industrial development in Indonesia, and what are the microeconomic firm dynamics driving this effect?", "study_design": "Longitudinal village-level panel with quasi-experimental instrumental variables (IV)", "methodology": "Two-stage least squares (2SLS) / IV exploiting colonial power plants and network distance", "population_or_unit": "Villages (desas) and manufacturing enterprises (IBS 20+ workers)", "geography": "Java, Indonesia", "data_sources": [ "Digitized PLN historical transmission and substation archives", "BPS Manufacturing Census (Survei Industri / IBS 1990-2000)", "BPS Podes (Potensi Desa) village infrastructure censuses" ], "key_findings": [ "Electricity grid expansion causally increases manufacturing firm counts, employment, and total output.", "Firm turnover (simultaneous entry and exit) is the primary structural mechanism.", "Output expansion is predominantly driven by new, higher-productivity entrants enabled by grid power.", "Electrification increases competitive pressure, raising exit rates among less efficient firms." ], "limitations": [ "Sample period is 1990–2000, preceding recent energy transition dynamics, nickel downstreaming, and renewable policy.", "Geographic scope is restricted to Java; does not evaluate Outer Island resource corridors." ], "research_gap": { "established": "Electricity grid access has a well-identified causal effect on manufacturing plant entry, productivity, and output in Java, Indonesia.", "uncertain": "Whether this historical causal relationship translates into high-frequency predictive information in modern quarterly PDRB nowcasts, or whether captive generation distorts that relationship in mineral-rich provinces.", "geographic_gap": "Focuses exclusively on Java; Outer Islands (Kalimantan, Sulawesi, Sumatra) with high captive generation shares remain unstudied.", "temporal_gap": "Ends at year 2000; lacks analysis of post-2015 industrial estate development and modern PLN tariff classes.", "data_gap": "Uses historical census panels; does not utilize modern high-frequency monthly PLN sales (Tarif Industri I1-I4) or quarterly PDRB time series.", "methodological_gap": "Employs annual long-run IV econometric estimation rather than mixed-frequency real-time nowcasting or machine learning models.", "proposed_contribution": "Research OS candidates build upon Kassem's causal foundation by testing short-run high-frequency nowcasting (Candidate 2) and modern industrial captive power penetration (Candidate 1)." }, "relevance_to_candidate": [ "cand-captive-power-industrial-transition", "cand-electricity-industrial-nowcasting" ] } }, { "schema_version": "1.0", "id": "lit-lehmann-2024-electricity-forecasting", "record_type": "canonical", "slug": "lehmann-2024-electricity-forecasting", "title": "Forecasting regional industrial production with novel high-frequency electricity consumption data", "authors": [ "Robert Lehmann", "Sascha Möhrle" ], "publication_year": 2024, "publication_type": "journal-article", "journal_or_venue": "Journal of Forecasting", "volume": "43", "issue": "6", "pages": "1918-1935", "publisher": "John Wiley & Sons, Inc.", "doi": "10.1002/for.3116", "url": "https://doi.org/10.1002/for.3116", "abstract": "In this paper, we study the predictive power of electricity consumption data for regional economic activity. Using unique weekly and monthly data for the Free State of Bavaria, Germany's second largest state, we run a pseudo out-of-sample forecasting experiment for the monthly growth rate of Bavarian industrial production. Electricity consumption turns out to be the best-performing indicator in our nowcasting setup and produces higher accuracy than conventional indicators in monthly forecasting experiments. Due to its high frequency, weekly electricity consumption gives a good prediction of the industrial activity in the current month with only one to two weeks of information. Regional electricity consumption is thus a promising avenue for measuring and forecasting regional economic activity.", "keywords": [ "Nowcasting", "Electricity consumption", "High-frequency data", "Industrial production", "Regional forecasting", "Pseudo-out-of-sample" ], "source_id": "src-scholarly-repository", "citation": "Lehmann, R., & Möhrle, S. (2024). Forecasting regional industrial production with novel high-frequency electricity consumption data. Journal of Forecasting, 43(6), 1918–1935. https://doi.org/10.1002/for.3116", "document_ids": [], "provenance": { "acquisition_method": "web", "source_classification": "scholarly", "source_name": "Journal of Forecasting (Wiley) & CESifo Working Paper No. 9917", "retrieved_at": "2026-09-16", "query_or_tool": "DOI resolver, Crossref metadata audit, and CESifo Working Paper No. 9917 documentation", "verification_status": "partially-verified" }, "verification_status": "partially-verified", "verification_details": { "metadata_verified": true, "content_verified": false, "research_interpretation_verified": false, "verified_by": "Solo Researcher", "verified_at": "2026-09-16", "notes": "Metadata verified via Crossref and Wiley catalog. Substantive methodology confirmed via CESifo Working Paper No. 9917 (2022) / ifo Institute documentation. Full primary journal article PDF not locally archived. Epistemic role: external empirical precedent (Bavaria, Germany); not direct evidence for Indonesia." }, "research_context": "Evaluates the incremental information value of high-frequency electricity consumption data for nowcasting monthly regional industrial production in Bavaria, Germany.", "methods_summary": "Real-time pseudo-out-of-sample forecasting design, bridge equation/nowcasting framework, evaluating forecast performance across forecast horizons and comparing against conventional business survey indicators.", "data_summary": "High-frequency weekly and monthly electricity consumption data from industrial firms and grid operators in Bavaria, paired with the official Bavarian monthly industrial production index.", "findings_summary": "High-frequency electricity consumption emerges as the best-performing indicator for nowcasting current-month regional industrial production, beating conventional survey benchmarks. Even 1–2 weeks of intra-month electricity data significantly reduce forecast errors. Predictive power is strongest for the current month (nowcasting) and attenuates for longer horizons.", "limitations_summary": "Empirical setting is Bavaria, Germany—a region with near-100% grid reliability, negligible off-grid captive coal power, and high administrative data quality. Does not account for captive generation signal distortion prevalent in developing countries.", "relevance_notes": "Primary methodological benchmark for candidate cand-electricity-industrial-nowcasting. Establishes empirical proof-of-concept that high-frequency electricity sales/consumption contain strong nowcasting signals for manufacturing output, while framing the Research OS gap: testing whether this relationship holds in Indonesia with quarterly PDRB and potential captive power distortion.", "literature_analysis": { "research_question": "Does novel high-frequency electricity consumption data improve nowcasts and short-term forecasts of regional industrial production compared to conventional benchmark indicators?", "study_design": "Pseudo-out-of-sample real-time forecasting experiment", "methodology": "Autoregressive distributed lag / bridge nowcasting models evaluated via root mean squared forecast error (RMSFE)", "population_or_unit": "Regional industrial sector (state-level aggregate)", "geography": "Bavaria, Germany", "data_sources": [ "Grid operator and industrial firm high-frequency electricity consumption records", "Bavarian State Statistical Office industrial production index" ], "key_findings": [ "Electricity consumption is the single best-performing indicator in the nowcasting experiment for regional industrial production.", "Intra-month weekly electricity data provide valuable leading signals within the current reference month.", "Electricity outperforms conventional business sentiment and survey indicators for current-month output.", "Predictive gain attenuates when extending the forecast horizon beyond the current month." ], "limitations": [ "Geographically restricted to an advanced European industrial state (Bavaria) with a highly stable interconnected grid.", "Does not address structural breaks from informal manufacturing or unmetered captive power self-generation." ], "research_gap": { "established": "High-frequency electricity consumption provides significant incremental predictive value for nowcasting regional industrial production in advanced economies with reliable grid metering.", "uncertain": "Whether electricity sales provide incremental predictive value for quarterly regional manufacturing PDRB in developing economies with publication vintages and captive power shares.", "geographic_gap": "Evaluated solely in Germany (Bavaria); unverified across emerging Southeast Asian regional economies.", "temporal_gap": "Covers monthly data up to 2021; does not reflect developing economy post-pandemic recovery patterns.", "data_gap": "Relied on German transmission/distribution metering; does not test Indonesian PLN sectoral sales (Tarif Industri I1-I4) vs BPS quarterly PDRB.", "methodological_gap": "Focused on monthly industrial production index; does not resolve quarterly-monthly mixed-frequency (MIDAS/DFM) nowcasting with Indonesian official release vintages.", "proposed_contribution": "Research OS candidate cand-electricity-industrial-nowcasting evaluates whether PLN industrial electricity sales improve real-time nowcasts of quarterly provincial manufacturing PDRB in Indonesia using a vintage-consistent out-of-sample design." }, "relevance_to_candidate": [ "cand-electricity-industrial-nowcasting" ] } }, { "schema_version": "1.0", "id": "lit-shehzadi-2024-self-generation", "record_type": "canonical", "slug": "shehzadi-2024-self-generation", "title": "Self-generation and outage losses: A firm-level analysis for emerging and developing Asian countries", "authors": [ "Anam Shehzadi", "Heike Wetzel" ], "publication_year": 2024, "publication_type": "journal-article", "journal_or_venue": "Energy Reports", "volume": "11", "pages": "2832-2840", "publisher": "Elsevier", "doi": "10.1016/j.egyr.2024.02.042", "url": "https://doi.org/10.1016/j.egyr.2024.02.042", "abstract": "Access to reliable and affordable electricity is critical to economic development in emerging and developing Asia. However, many firms in these regions face challenges in obtaining consistent and affordable electricity from the grid, leading them to invest in self-generation technologies. This paper examines the strategic decision of firms to self-generate electricity and the economic losses incurred during power outages. Using survey data from the World Bank Enterprise Survey (WBES) of 5639 manufacturing firms in seven Asian countries, we identify factors driving the decision to self-generate and assess the impact of self-generation on mitigating economic losses during power outages. An endogenous switching regression model is employed to account for self-selection bias. The results show that firms experiencing more outages and higher electricity costs are more likely to invest in self-generation. Larger, older, and exporting firms also show a higher propensity to self-generate. In addition, the results indicate that firms that invested in self-generation would have experienced, on average, outage losses that were 88 percent higher than their actual losses if they had not invested. Conversely, firms without self-generation could have reduced their actual outage losses by on average 5 percent by implementing self-generation strategies. Overall, our results indicate that self-generating firms in Asian emerging and developing countries are particularly vulnerable to losses from power outages and underscore the importance of self-generation as a strategic choice for these firms.", "keywords": [ "Power outages", "Self-generation", "Outage losses", "Endogenous switching regression model", "Manufacturing firms", "Indonesia" ], "source_id": "src-scholarly-repository", "citation": "Shehzadi, A., & Wetzel, H. (2024). Self-generation and outage losses: A firm-level analysis for emerging and developing Asian countries. Energy Reports, 11, 2832–2840. https://doi.org/10.1016/j.egyr.2024.02.042", "document_ids": [ "doc-shehzadi-2024-self-generation" ], "provenance": { "acquisition_method": "file", "source_classification": "scholarly", "source_name": "Energy Reports (Elsevier Open Access)", "retrieved_at": "2026-09-16", "query_or_tool": "Direct PDF inspection and text extraction from documents/pdf/shehzadi-and-wetzel-2024.pdf", "verification_status": "verified" }, "verification_status": "verified", "verification_details": { "metadata_verified": true, "content_verified": true, "research_interpretation_verified": false, "verified_by": "Solo Researcher", "verified_at": "2026-09-16", "notes": "Full primary PDF inspected and validated. Verified 5,639 manufacturing firms in WBES across 7 Asian countries, including Indonesia (~42% generator ownership; ATU -25% potential loss reduction). Interpretation remains provisional pending human audit." }, "research_context": "Investigates firm-level drivers of self-generation and the economic loss mitigation effect during power outages across seven Asian emerging and developing economies (Bangladesh, China, India, Indonesia, Myanmar, Philippines, Sri Lanka).", "methods_summary": "Employs an Endogenous Switching Regression Model (ESRM) to control for unobserved self-selection bias in self-generation decisions, estimating ATT and ATU for outage losses (% of sales).", "data_summary": "World Bank Enterprise Survey (WBES) microdata for 5,639 manufacturing firms, measuring power outage occurrence, outage losses (% annual sales), electricity expenditure, firm size, age, ownership, and export status.", "findings_summary": "Outage frequency and electricity cost significantly increase the probability of investing in self-generation. Larger, older, and export-oriented firms have higher self-generation propensity. Self-generating firms would face 88% higher outage losses without self-generation (ATT); non-self-generating firms could reduce outage losses by 5% overall (ATU), and by 25% specifically in Indonesia.", "limitations_summary": "Focuses on binary generator ownership and generic self-generation. Does not distinguish large-scale industrial captive power plants (e.g. mineral smelters) from backup diesel generators. Does not observe captive capacity in MW or generation intensity in MWh.", "relevance_notes": "Crucial empirical precedent for candidate cand-captive-power-industrial-transition. Clarifies that determinants of generic firm self-generation are already established in recent literature, narrowing the viable Research OS gap to plant-scale captive intensity, subsector variation, and regional grid reliability in Indonesia.", "literature_analysis": { "research_question": "What factors drive manufacturing firms to self-generate electricity in emerging Asian countries, and does self-generation effectively mitigate economic losses from power outages?", "study_design": "Cross-sectional microeconometric analysis with endogenous switching regression", "methodology": "Endogenous Switching Regression Model (ESRM) with full information maximum likelihood", "population_or_unit": "Manufacturing firms (WBES enterprise level)", "geography": "Emerging and developing Asia (Bangladesh, China, India, Indonesia, Myanmar, Philippines, Sri Lanka)", "data_sources": [ "World Bank Enterprise Survey (WBES)" ], "key_findings": [ "Firms experiencing more frequent outages and higher electricity costs are significantly more likely to self-generate.", "Firm size, age, and export participation increase the likelihood of self-generation.", "Average generator ownership in Indonesia is approximately 42% among surveyed manufacturing firms.", "In Indonesia, firms without self-generation could have reduced average outage losses by 25% if they had adopted self-generation (ATU = -25%)." ], "limitations": [ "Measures self-generation as a binary indicator (owns or shares a generator), omitting capacity (MW) and energy share (MWh).", "Does not capture industrial captive power plants dedicated to heavy process industries (e.g. coal-fired smelter captive plants)." ], "research_gap": { "established": "Outage frequency, electricity costs, and firm scale/export status are significant determinants of generic firm self-generation and outage mitigation in Asian emerging markets including Indonesia.", "uncertain": "Whether large-scale industrial captive generation intensity is driven by the same reliability/cost factors as generic backup generation, or by structural grid constraints and process-specific energy demands.", "geographic_gap": "Evaluates national-level pooled samples without analyzing Indonesian provincial or industrial estate geographical clustering.", "temporal_gap": "Relies on pre-2023 WBES survey waves; does not capture the recent post-2020 critical mineral downstreaming and industrial captive boom.", "data_gap": "Uses WBES survey sample rather than comprehensive census microdata (BPS IBS) covering energy inputs and captive generation capacity.", "methodological_gap": "Models binary decision via ESRM rather than continuous captive generation intensity and fuel technology choice.", "proposed_contribution": "Research OS candidate cand-captive-power-industrial-transition evaluates industrial captive power intensity and fuel choice across Indonesian provinces using BPS IBS microdata and regional PLN grid metrics." }, "relevance_to_candidate": [ "cand-captive-power-industrial-transition" ] } } ], "documents": [ { "schema_version": "1.0", "id": "doc-chojkiewicz-2025-solar-storage-captive", "record_type": "canonical", "filename": "chojkiewicz-et-al-2025.pdf", "mime_type": "application/pdf", "sha256": "f17945ecc5d165985d6dad57aed43bbd3746d9c4b780da8a2406a7580ac4e96a", "file_size_bytes": 5774841, "storage": { "uri": "documents/pdf/chojkiewicz-et-al-2025.pdf", "backend": "local" }, "title_as_documented": "Declining costs make solar plus storage economical for industrial captive power", "page_count": 12, "language": "en", "source_reference": "iScience, Volume 28, Issue 11, Article 113763, November 21, 2025 (Elsevier Open Access)", "integrity_status": "intact", "extraction": { "status": "success", "method": "pdf-text", "tool": "pdftotext", "extracted_at": "2026-09-16", "notes": "Full text successfully extracted from primary PDF; 12 pages verified." }, "provenance": { "acquisition_method": "file", "source_name": "iScience (Elsevier Open Access)", "acquired_at": "2026-09-16", "notes": "Primary PDF binary verified locally in documents/pdf/." }, "verification_status": "verified", "acquired_at": "2026-09-16", "notes": "Cryptographic hash SHA-256 and byte size verified from physical disk file. Document artifact represents physical file integrity, not scientific truth of claims." }, { "schema_version": "1.0", "id": "doc-shehzadi-2024-self-generation", "record_type": "canonical", "filename": "shehzadi-and-wetzel-2024.pdf", "mime_type": "application/pdf", "sha256": "b676368504d4aa31e57a91afd34dfa6d965466c3284d2f08e46c92e9353f5b99", "file_size_bytes": 785463, "storage": { "uri": "documents/pdf/shehzadi-and-wetzel-2024.pdf", "backend": "local" }, "title_as_documented": "Self-generation and outage losses: A firm-level analysis for emerging and developing Asian countries", "page_count": 9, "language": "en", "source_reference": "Energy Reports, Volume 11, 2024, pp. 2832-2840 (Elsevier / ScienceDirect Open Access)", "integrity_status": "intact", "extraction": { "status": "success", "method": "pdf-text", "tool": "pdftotext", "extracted_at": "2026-09-16", "notes": "Full text successfully extracted from primary PDF; 9 pages verified." }, "provenance": { "acquisition_method": "file", "source_name": "Energy Reports (Elsevier Open Access)", "acquired_at": "2026-09-16", "notes": "Primary PDF binary verified locally in documents/pdf/." }, "verification_status": "verified", "acquired_at": "2026-09-16", "notes": "Cryptographic hash SHA-256 and byte size verified from physical disk file. Document artifact represents physical file integrity, not scientific truth of claims." } ], "projects": [], "experiments": [], "findings": [], "evidence": [ { "schema_version": "1.0", "id": "ev-bps-electricity-nowcasting-feasibility-audit", "project_slug": null, "title": "Audit Kelayakan Empiris Electricity Layer untuk Nowcasting PDRB Manufaktur Provinsi (Status: BLOCKED)", "type": "empirical", "source_id": "src-bps", "provenance": { "acquisition_method": "bps_mcp", "source_type": "bps_mcp", "source_name": "BPS WebAPI v1 & Katalog Publikasi Statistik Listrik", "retrieved_at": "2026-09-16", "query_or_tool": "BPS WebAPI Var 314, Var 859, Domain 3100, 3200, 3500 & Publikasi Statistik Listrik 2020-2024", "verification_status": "verified" }, "dataset_id": "ds-bps-electricity-consumption-generation", "reference": "BPS WebAPI v1 (Var 314, Var 859, Domain 3100 Var 181/178, Domain 3200 Var 408, Domain 3500 Var 566) & Publikasi Statistik Listrik 2020-2024 (ID c4f7aade5d4801236ec79b81, Rilis 2025-12-31)", "excerpt": "Audit empiris live terhadap portal data BPS membuktikan bahwa data penjualan/konsumsi listrik industri resmi hanya tersedia pada frekuensi tahunan nasional (Var 314) atau total konsumsi provinsi tanpa pemisahan industri (Var 859). Portal daerah terfragmentasi atau mati (Jabar Var 408 berhenti 2019, Jatim Var 566 berhenti 2021), dan publikasi resmi ber-lag 12 bulan (T+12 bulan; edisi 2020-2024 baru rilis 31 Desember 2025). Oleh karena itu, Electricity Layer BLOCKED sebagai predictor utama real-time high-frequency provincial nowcasting. Bukti empiris dan literatur kelistrikan historis tetap valid sebagai konteks screening dan analisis struktural tahunan terpisah.", "confidence": "high", "retrieved_at": "2026-09-16", "verification_status": "verified" }, { "schema_version": "1.0", "id": "ev-bps-provincial-export-imk-nowcasting-audit", "project_slug": null, "title": "Audit Kelayakan Indikator Pengganti: Ekspor Nonmigas Provinsi (Var 2346) & IMK (Var 401)", "type": "empirical", "source_id": "src-bps", "provenance": { "acquisition_method": "bps_mcp", "source_type": "bps_mcp", "source_name": "BPS WebAPI v1 & Kalender Berita Resmi Statistik (BRS)", "retrieved_at": "2026-09-16", "query_or_tool": "BPS WebAPI v1 Var 2346, Var 401, Var 89, Var 2267 & BRS Ekspor/PDRB", "verification_status": "verified" }, "dataset_id": "ds-bps-pdrb-structural-transformation", "reference": "BPS WebAPI v1 (Var 2346, Var 401, Var 89, Var 2267) & Kalender Rilis BRS BPS 2024", "excerpt": "Audit kelayakan empiris membuktikan bahwa Nilai Ekspor Nonmigas Bulanan Menurut Provinsi Asal Barang (Var 2346, 2022-2026) tersedia lengkap untuk 38 provinsi dan terbit mendahului rilis PDRB triwulanan (contoh aktual 2024: ekspor Maret rilis 22 April 2024 vs PDRB Q1 rilis 6 Mei 2024, memberikan lead time 14 hari). Ekspor provinsi diposisikan sebagai proxy aktivitas ekonomi/industri daerah, bukan pengukuran langsung output manufaktur fisik. Status prediktor Var 2346 tetap CONDITIONAL sampai full vintage ingestion selesai; Var 401 (IMK) tetap CONDITIONAL sampai pola revisi diverifikasi; target Var 2267 terverifikasi pada level sampel vintage namun basis data vintage historis belum selesai. Oleh karena itu, tahap pemodelan empiris tetap GATED.", "confidence": "high", "retrieved_at": "2026-09-16", "verification_status": "verified" }, { "schema_version": "1.0", "id": "ev-bps-stat-listrik", "project_slug": null, "title": "Publikasi Resmi BPS Statistik Listrik 2020-2024", "type": "publication", "source_id": "src-bps", "provenance": { "acquisition_method": "bps_mcp", "source_type": "bps_mcp", "source_name": "Publikasi BPS Statistik Listrik 2020-2024", "retrieved_at": "2026-09-13", "query_or_tool": "BPS MCP bps-statistics query publikasi 2354-6875", "verification_status": "verified" }, "dataset_id": "ds-bps-electricity-consumption-generation", "reference": "Publikasi BPS No. Publikasi 2354-6875 (Rilis 2025-12-31)", "excerpt": "Survei Tahunan Perusahaan Listrik BPS menyajikan kapasitas terpasang pembangkit, produksi tenaga listrik neto dan bruto, susut transmisi-distribusi, serta rincian penjualan tenaga listrik menurut kelompok tarif rumah tangga, industri, dan bisnis.", "confidence": "high", "retrieved_at": "2026-09-13", "verification_status": "verified" }, { "schema_version": "1.0", "id": "ev-bps-table-1555", "project_slug": null, "title": "BPS Tabel Statis 1555 Persentase Rumah Tangga menurut Provinsi dan Penerangan Listrik PLN", "type": "statistic", "source_id": "src-bps", "provenance": { "acquisition_method": "bps_mcp", "source_type": "bps_mcp", "source_name": "BPS Static Table 1555 (Susenas)", "retrieved_at": "2026-09-13", "query_or_tool": "BPS MCP get_static_table 1555", "verification_status": "verified" }, "dataset_id": "ds-bps-electricity-access-panel", "reference": "BPS WebAPI & Static Table No. 1555 (Susenas 1993–2022)", "excerpt": "Persentase rumah tangga dengan sumber penerangan listrik PLN menurut provinsi mencatat disparitas historis dari 1993 hingga 2022 pada 34 provinsi di Indonesia.", "confidence": "high", "retrieved_at": "2026-09-13", "verification_status": "verified" }, { "schema_version": "1.0", "id": "ev-bps-vintage-first-release-revision-audit", "project_slug": null, "title": "Kuantifikasi Revisi Empiris First-Release vs Current API & Limitasi Vintage BPS", "type": "empirical", "source_id": "src-bps", "provenance": { "acquisition_method": "bps_mcp", "source_type": "bps_mcp", "source_name": "BRS BPS No. 14/02/Th. XXVII & BPS WebAPI v1 Var 2346", "retrieved_at": "2026-09-16", "query_or_tool": "Perbandingan First-Release BRS PDF (15 Feb 2024) vs Current WebAPI v1 (Sep 2026)", "verification_status": "verified" }, "dataset_id": "ds-bps-pdrb-structural-transformation", "reference": "Berita Resmi Statistik No. 14/02/Th. XXVII (15 Februari 2024) vs BPS WebAPI v1 Var 2346 datacontent", "excerpt": "Perbandingan nilai ekspor Januari 2024 pada 7 provinsi sampel membuktikan bahwa Current API mengalami revisi rutin ke bawah (-0,40% s.d. -13,84%) dibanding nilai first-release BRS: Jawa Barat (US$ 2.946,0M vs 2.906,56M, revisi -1,34%), Jawa Tengah (US$ 935,5M vs 931,78M, -0,40%), Jawa Timur (US$ 1.985,9M vs 1.896,98M, -4,48%), Banten (US$ 1.051,7M vs 1.041,45M, -0,97%), Kepulauan Riau (US$ 1.228,9M vs 1.132,13M, -7,87%), Kalimantan Timur (US$ 2.170,7M vs 1.870,20M, -13,84%), dan Sulawesi Tengah (US$ 1.745,2M vs 1.622,24M, -7,05%). Menggunakan data Current API secara langsung memicu revision leakage. Backtesting pseudo-out-of-sample wajib menggunakan rekonstruksi first-release dari BRS. Verifikasi audit membuktikan fenomena revisi secara empiris, namun basis data vintage historis belum selesai dibangun dan pemodelan empiris tetap GATED.", "confidence": "high", "retrieved_at": "2026-09-16", "verification_status": "verified" }, { "schema_version": "1.0", "id": "ev-den-rued-gap-audit", "project_slug": null, "title": "Audit Ketercukupan & Jeda Publikasi Data Realisasi RUED-P Daerah DEN", "type": "official_source", "source_id": "src-den", "provenance": { "acquisition_method": "file", "source_type": "file", "source_name": "Dewan Energi Nasional (DEN)", "retrieved_at": "2026-09-13", "query_or_tool": "Audit dokumen fisik PDF Buku Bauran Energi DEN 2022 & Repositori Perda RUED", "verification_status": "partially-verified" }, "dataset_id": "ds-esdm-ebt-regional-balance", "reference": "Publikasi Dewan Energi Nasional: Buku Bauran Energi Nasional 2022 & Repositori Perda RUED Provinsi (den.go.id/publikasi/rued-provinsi)", "excerpt": "Pemeriksaan dokumen resmi DEN mengonfirmasi jeda publikasi (reporting lag) 1-2 tahun untuk data evaluasi komparatif daerah (laporan komparatif terbuka nasional terakhir tahun 2022). Sekitar 30 provinsi telah mengesahkan Perda RUED, namun terjadi asimetri di mana provinsi seperti Kalimantan Timur dan klaster pemekaran DOB Papua mengalami kekosongan data resmi.", "confidence": "medium", "retrieved_at": "2026-09-13", "verification_status": "partially-verified" }, { "schema_version": "1.0", "id": "ev-ga-energy-audit", "project_slug": null, "title": "Audit Sinyal Pencarian Energi Google Analytics Property 553910715", "type": "observation", "source_id": "src-ga", "provenance": { "acquisition_method": "ga_mcp", "source_type": "ga_mcp", "source_name": "Google Analytics 4 Property 553910715", "retrieved_at": "2026-09-13", "query_or_tool": "GA4 RunReport searchTerm query", "verification_status": "verified" }, "reference": "Google Analytics 4 RunReport Query (2024-01-01 s.d. 2026-09-13)", "excerpt": "Pemeriksaan query searchTerm untuk istilah 'panel surya', 'PLTS atap', dan 'energi terbarukan' pada properti Research OS mencatat 0 baris data / 0 active users, mengonfirmasi ketiadaan sinyal organik internal dan perlunya bertumpu pada bukti empiris BPS.", "confidence": "high", "retrieved_at": "2026-09-13", "verification_status": "verified" }, { "schema_version": "1.0", "id": "ev-lit-burke-captive-barrier", "project_slug": null, "title": "Temuan Literatur Hambatan Captive Power terhadap Dekarbonisasi Listrik Nasional", "type": "literature", "source_id": "src-scholarly-repository", "literature_id": "lit-burke-2019-indonesia-electricity", "document_id": null, "reference": "Burke & Abdurrahman (2019), Energy Policy, Vol. 131, pp. 388-397", "excerpt": "Off-grid captive power generation, predominantly coal-fired in industrial estates and mineral processing smelters, expanded rapidly and created institutional resistance against grid-connected renewable power purchase agreements.", "location": { "url": "https://doi.org/10.1016/j.enpol.2019.04.034" }, "confidence": "high", "retrieved_at": "2026-09-14", "verification_status": "partially-verified", "provenance": { "acquisition_method": "web", "source_type": "web", "source_classification": "scholarly", "source_name": "Energy Policy (Elsevier)", "retrieved_at": "2026-09-14", "query_or_tool": "DOI / Crossref citation audit. Page/table locators removed: physical PDF artifact was a dummy fixture no longer available.", "verification_status": "partially-verified" } }, { "schema_version": "1.0", "id": "ev-lit-chojkiewicz-captive-coal-scale", "project_slug": null, "title": "Skala dan Pertumbuhan Kapasitas Pembangkit Captive Batu Bara Industri di Indonesia", "type": "literature", "source_id": "src-scholarly-repository", "literature_id": "lit-chojkiewicz-2025-solar-storage-captive", "document_id": "doc-chojkiewicz-2025-solar-storage-captive", "reference": "Chojkiewicz et al. (2025), iScience, Vol. 28, Issue 11, Article 113763", "excerpt": "Over the past decade, captive coal capacity has grown 8-fold, reaching 11 GW in 2023, with another 14 GW remaining proposed or in development. The majority of this captive coal capacity serves the metal processing industry - including nickel, cobalt and aluminum smelters - which have been promoted by the government alongside bans of unrefined metal ores in an effort to turn Indonesia into a manufacturing hub for batteries and electric vehicles.", "location": { "document_id": "doc-chojkiewicz-2025-solar-storage-captive", "page": 2, "journal_page": 2, "pdf_page": 2, "section": "Introduction", "paragraph": 2 }, "confidence": "high", "retrieved_at": "2026-09-16", "verification_status": "verified", "provenance": { "acquisition_method": "file", "source_classification": "scholarly", "source_name": "iScience (Elsevier Open Access)", "retrieved_at": "2026-09-16", "query_or_tool": "Direct PDF inspection and text extraction from documents/pdf/chojkiewicz-et-al-2025.pdf", "verification_status": "verified" } }, { "schema_version": "1.0", "id": "ev-lit-chojkiewicz-solar-storage-lcoe", "project_slug": null, "title": "Hasil Pemodelan Tekno-Ekonomi: Paritas Biaya LCOE Solar Plus Storage terhadap Captive Batu Bara di Kalimantan", "type": "literature", "source_id": "src-scholarly-repository", "literature_id": "lit-chojkiewicz-2025-solar-storage-captive", "document_id": "doc-chojkiewicz-2025-solar-storage-captive", "reference": "Chojkiewicz et al. (2025), iScience, Vol. 28, Issue 11, Article 113763", "excerpt": "Here we assess the rapidly growing region of Kalimantan and show how, with targeted support policies, the co-location of solar PV generation with battery storage can achieve a Levelized Cost of Energy (LCOE) of 5.6–7.9 cents/kWh at present, varying with capacity factor and financing conditions, competitive with conventional captive coal generation for industrial applications... Co-location with solar cuts storage costs by up to 20% versus standalone deployment.", "location": { "document_id": "doc-chojkiewicz-2025-solar-storage-captive", "page": "1, 5", "journal_page": "1, 5", "pdf_page": "1, 5", "section": "Summary & Highlights (p. 1) & Techno-economic assessment results (p. 5)", "paragraph": 1 }, "confidence": "high", "retrieved_at": "2026-09-16", "verification_status": "verified", "provenance": { "acquisition_method": "file", "source_classification": "scholarly", "source_name": "iScience (Elsevier Open Access)", "retrieved_at": "2026-09-16", "query_or_tool": "Direct PDF inspection and text extraction from documents/pdf/chojkiewicz-et-al-2025.pdf", "verification_status": "verified" } }, { "schema_version": "1.0", "id": "ev-lit-kassem-grid-industrial-turnover", "project_slug": null, "title": "Pengaruh Kausal Ekspansi Jaringan Listrik terhadap Perkembangan Industri dan Perputaran Perusahaan (Firm Turnover) di Jawa", "type": "literature", "source_id": "src-scholarly-repository", "literature_id": "lit-kassem-2024-electrification-industrial-development", "document_id": null, "reference": "Kassem (2024), Journal of Development Economics, Vol. 167, 103234", "excerpt": "I ask whether electrification causes industrial development. I combine newly digitized data from the Indonesian state electricity company with rich manufacturing census data. To understand how electrification can cause industrial development, I shed light on an important economic mechanism — firm turnover. In particular, I study the effect of the extensive margin of electrification (grid expansion) on the extensive margin of industrial development (firm entry and exit). To deal with endogenous grid placement, I use an instrumental variable approach exploiting the location of colonial electric infrastructure and the need for an interconnected grid on the island of Java. I find that electrification causes industrial development by increasing the number of manufacturing firms, manufacturing workers, and manufacturing output. Electrification increases firm entry rates, but also exit rates, and entry accounts for most of the increase in output. This is consistent with electrification lowering entry costs, increasing competition, and forcing unproductive firms to exit more often.", "location": { "url": "https://doi.org/10.1016/j.jdeveco.2023.103234", "section": "Publisher Abstract (Elsevier / ScienceDirect) & Supporting IGC Working Paper Context", "journal_page": "103234", "pdf_page": null }, "confidence": "high", "retrieved_at": "2026-09-16", "verification_status": "partially-verified", "provenance": { "acquisition_method": "web", "source_classification": "scholarly", "source_name": "Journal of Development Economics (Elsevier ScienceDirect) & IGC Working Paper Series", "retrieved_at": "2026-09-16", "query_or_tool": "ScienceDirect publisher abstract, Crossref DOI resolver, and IGC / VoxDev / CRC TR 224 research summaries", "verification_status": "partially-verified" } }, { "schema_version": "1.0", "id": "ev-lit-lehmann-electricity-nowcasting-precedent", "project_slug": null, "title": "Preseden Metodologis Nowcasting Produksi Industri Regional Berbasis Data Listrik Frekuensi Tinggi di Bavaria", "type": "literature", "source_id": "src-scholarly-repository", "literature_id": "lit-lehmann-2024-electricity-forecasting", "document_id": null, "reference": "Lehmann & Möhrle (2024), Journal of Forecasting, Vol. 43(6), pp. 1918-1935 / CESifo Working Paper No. 9917", "excerpt": "In this paper, we study the predictive power of electricity consumption data for regional economic activity. Using unique weekly and monthly data for the Free State of Bavaria, Germany's second largest state, we run a pseudo out-of-sample forecasting experiment for the monthly growth rate of Bavarian industrial production. Electricity consumption turns out to be the best-performing indicator in our nowcasting setup and produces higher accuracy than conventional indicators in monthly forecasting experiments. Due to its high frequency, weekly electricity consumption gives a good prediction of the industrial activity in the current month with only one to two weeks of information.", "location": { "url": "https://doi.org/10.1002/for.3116", "section": "Abstract / Section 1 (Journal & CESifo Working Paper No. 9917)", "journal_page": "1918-1935", "pdf_page": null }, "confidence": "high", "retrieved_at": "2026-09-16", "verification_status": "partially-verified", "provenance": { "acquisition_method": "web", "source_classification": "scholarly", "source_name": "Journal of Forecasting (Wiley) & CESifo Working Paper No. 9917", "retrieved_at": "2026-09-16", "query_or_tool": "DOI resolver, Crossref metadata audit, and CESifo Working Paper No. 9917 project documentation", "verification_status": "partially-verified" } }, { "schema_version": "1.0", "id": "ev-lit-shehzadi-indonesia-generator-losses", "project_slug": null, "title": "Tingkat Kepemilikan Pembangkit Mandiri dan Potensi Reduksi Kerugian Pemadaman di Indonesia", "type": "literature", "source_id": "src-scholarly-repository", "literature_id": "lit-shehzadi-2024-self-generation", "document_id": "doc-shehzadi-2024-self-generation", "reference": "Shehzadi & Wetzel (2024), Energy Reports, Vol. 11, pp. 2832-2840", "excerpt": "Section 3 (p. 2834): 'Nevertheless, the observed lowest percentage of companies owning a generator is still relatively high with about 42 percent in Indonesia.' Section 5 (p. 2837): 'On the other hand, the estimated ATU for firms without self-generation indicates that firms in China, India, and Indonesia could have reduced their average outage losses by 16 percent, 5 percent, and 25 percent, respectively, if they had invested in self-generation.'", "location": { "document_id": "doc-shehzadi-2024-self-generation", "page": "2834, 2837", "journal_page": "2834, 2837", "pdf_page": "3, 6", "section": "Section 3. Data (p. 2834) & Section 5. 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